Simulace.info - User contributions [en]

File:Slime mold.nlogo

2019-01-24T14:08:43Z

Kadj02: The NetLogo simulation file

== Summary ==
The NetLogo simulation file

Slime mold

2019-01-24T14:08:21Z

Kadj02: /* Code */

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. [[File:run_down1.jpg|Successful rundown|center|500px|]] There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. [[File:mold_found_food.jpg|Mold found food|center|500px|]]
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. [[File:5_origins_points.jpg|Simulation with 5 random origin points|center|500px|]] - red are the dry ones, green are the healthy ones 

Sadly considering the nature of spreading of this mold there is an area given by the inner circle of the square-world, which formulates an impenetrable layer. There is a trigger for this in code, however in the random generated origins scenario there is a high possibility of triggering this very early in to simulation. [[File:edge_of_radius.jpg|Edge of the world|center|500px|]]

==Numeric results==
Considering the nature of our simulation I decided to do extensive experimenting only with one point of origin in the center. Other alternatives were way too inconsistent considering so many depending variables were random generated. Together with the random motion of particles it was nearly impossible to derive any meaningful results.
For the conservative scenario there is threshold around 4000 units of mold-resource, where doesn’t really matter if there are any food present.
Everything above 4000 units of mold-resource is very depended on the number, strength and location of the food.
Above 25000 – 35000 units of mold-resource is almost certain that mold will consume all the food in the world.
And above 90000 there is for mold not really need for food to be present in the world whatsoever.
The effectiveness of the spores seems to be something below 20% - which means more than 80% spores die because they wander off the world’s edge.

=Conclusion=
The simulation were successful in replicating the pattern of the slime mold with the help of DLA algorithm. Unfortunately there were several issues with the simulation on the technical side as well as on the simulation side.
The possibilities with randomizing points of origins turned out to be not useful at all for drawing any meaningful conclusions. The world is very limited and therefore the patches has to be shrinked down by a lot. That leads in simulations with ending at some millionth tick. Adding that the number of particles in this world that needs to be redrawn every cycle leads to a very heavy computing power-hungry simulation.

=Code=
External source: https://uloz.to/!Hf0bjuUH3dCS/slime-mold-nlogo

Internal source: [[File:slime_mold.nlogo]]

Slime mold

2019-01-24T14:07:22Z

Kadj02: /* Results */

File:Edge of radius.jpg

2019-01-24T14:06:47Z

Kadj02: There is a limiting circle in the simulation caused by the genereted agents

== Summary ==
There is a limiting circle in the simulation caused by the genereted agents

Slime mold

2019-01-24T14:05:49Z

Kadj02: /* Results */

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. [[File:run_down1.jpg|Successful rundown|center|500px|]] There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. [[File:mold_found_food.jpg|Mold found food|center|500px|]]
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. [[File:5_origins_points.jpg|Simulation with 5 random origin points|center|500px|]] - red are the dry ones, green are the healthy ones

Sadly considering the nature of spreading of this mold there is an area given by the inner circle of the square-world, which formulates an impenetrable layer. There is a trigger for this in code, however in the random generated origins scenario there is a high possibility of triggering this very early in to simulation. [[File:edge_of_radius.jpg|Edge of the world|center|500px|]]

==Numeric results==
Considering the nature of our simulation I decided to do extensive experimenting only with one point of origin in the center. Other alternatives were way too inconsistent considering so many depending variables were random generated. Together with the random motion of particles it was nearly impossible to derive any meaningful results.
For the conservative scenario there is threshold around 4000 units of mold-resource, where doesn’t really matter if there are any food present.
Everything above 4000 units of mold-resource is very depended on the number, strength and location of the food.
Above 25000 – 35000 units of mold-resource is almost certain that mold will consume all the food in the world.
And above 90000 there is for mold not really need for food to be present in the world whatsoever.
The effectiveness of the spores seems to be something below 20% - which means more than 80% spores die because they wander off the world’s edge.

=Conclusion=
The simulation were successful in replicating the pattern of the slime mold with the help of DLA algorithm. Unfortunately there were several issues with the simulation on the technical side as well as on the simulation side.
The possibilities with randomizing points of origins turned out to be not useful at all for drawing any meaningful conclusions. The world is very limited and therefore the patches has to be shrinked down by a lot. That leads in simulations with ending at some millionth tick. Adding that the number of particles in this world that needs to be redrawn every cycle leads to a very heavy computing power-hungry simulation.

=Code=
https://uloz.to/!Hf0bjuUH3dCS/slime-mold-nlogo

File:5 origins points.jpg

2019-01-24T14:04:35Z

Kadj02: A point in time of simulation, where 2 branches of the mold are blocked by more prominent branches

== Summary ==
A point in time of simulation, where 2 branches of the mold are blocked by more prominent branches

Slime mold

2019-01-24T14:03:51Z

Kadj02: /* Results */

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. [[File:run_down1.jpg|Successful rundown|center|500px|]] There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. [[File:mold_found_food.jpg|Mold found food|center|500px|]]
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. [[File:5_origins_points.jpg|Simulation with 5 random origin points|center|500px|]] - red are the dry ones, green are the healthy ones

Sadly considering the nature of spreading of this mold there is an area given by the inner circle of the square-world, which formulates an impenetrable layer. There is a trigger for this in code, however in the random generated origins scenario there is a high possibility of triggering this very early in to simulation. ( https://imgur.com/a/AW1crvA )

==Numeric results==
Considering the nature of our simulation I decided to do extensive experimenting only with one point of origin in the center. Other alternatives were way too inconsistent considering so many depending variables were random generated. Together with the random motion of particles it was nearly impossible to derive any meaningful results.
For the conservative scenario there is threshold around 4000 units of mold-resource, where doesn’t really matter if there are any food present.
Everything above 4000 units of mold-resource is very depended on the number, strength and location of the food.
Above 25000 – 35000 units of mold-resource is almost certain that mold will consume all the food in the world.
And above 90000 there is for mold not really need for food to be present in the world whatsoever.
The effectiveness of the spores seems to be something below 20% - which means more than 80% spores die because they wander off the world’s edge.

=Conclusion=
The simulation were successful in replicating the pattern of the slime mold with the help of DLA algorithm. Unfortunately there were several issues with the simulation on the technical side as well as on the simulation side.
The possibilities with randomizing points of origins turned out to be not useful at all for drawing any meaningful conclusions. The world is very limited and therefore the patches has to be shrinked down by a lot. That leads in simulations with ending at some millionth tick. Adding that the number of particles in this world that needs to be redrawn every cycle leads to a very heavy computing power-hungry simulation.

=Code=
https://uloz.to/!Hf0bjuUH3dCS/slime-mold-nlogo

File:Mold found food.jpg

2019-01-24T14:01:09Z

Kadj02: Displaying on plot in what time mold found new resources

== Summary ==
Displaying on plot in what time mold found new resources

Slime mold

2019-01-24T14:00:32Z

Kadj02: /* Results */

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. [[File:run_down1.jpg|Successful rundown|center|500px|]] There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. [[File:mold_found_food.jpg|Mold found food|center|500px|]]
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. ( https://imgur.com/a/gkyCTwN - red are the dry ones, green are the healthy ones )

Sadly considering the nature of spreading of this mold there is an area given by the inner circle of the square-world, which formulates an impenetrable layer. There is a trigger for this in code, however in the random generated origins scenario there is a high possibility of triggering this very early in to simulation. ( https://imgur.com/a/AW1crvA )

==Numeric results==
Considering the nature of our simulation I decided to do extensive experimenting only with one point of origin in the center. Other alternatives were way too inconsistent considering so many depending variables were random generated. Together with the random motion of particles it was nearly impossible to derive any meaningful results.
For the conservative scenario there is threshold around 4000 units of mold-resource, where doesn’t really matter if there are any food present.
Everything above 4000 units of mold-resource is very depended on the number, strength and location of the food.
Above 25000 – 35000 units of mold-resource is almost certain that mold will consume all the food in the world.
And above 90000 there is for mold not really need for food to be present in the world whatsoever.
The effectiveness of the spores seems to be something below 20% - which means more than 80% spores die because they wander off the world’s edge.

=Conclusion=
The simulation were successful in replicating the pattern of the slime mold with the help of DLA algorithm. Unfortunately there were several issues with the simulation on the technical side as well as on the simulation side.
The possibilities with randomizing points of origins turned out to be not useful at all for drawing any meaningful conclusions. The world is very limited and therefore the patches has to be shrinked down by a lot. That leads in simulations with ending at some millionth tick. Adding that the number of particles in this world that needs to be redrawn every cycle leads to a very heavy computing power-hungry simulation.

=Code=
https://uloz.to/!Hf0bjuUH3dCS/slime-mold-nlogo

Optimal size of HDD for virtual Digitization server

2019-01-24T13:58:57Z

Kadj02: Undo revision 17362 by Kadj02 (talk)

=Introduction=

Proper usage of server space and capacity is very important for companies these days as the volume of data gathered and produced is growing rapidly and is essential for proper operation of modern companies.
This simulation is designed to calculate optimal HDD size for a server which is used for processing documents and is based on real data obtained from a company production server.

=Problem definition=
The simulation is based on data gathered by a server application in database, observations of the server (mainly focused on batch count and their size) and additional information about the solution running on the server gathered from documentation:
*Processing takes place only on work days
*Every document scanned to the server is processed by a digitization application which creates batch that contains original scanned document, extracted data in XML files, log files, enhanced images and searchable PDF
*Application saves all important information about batches in database
*Backup images from scanning will stay on the server for 6 months (those are additional ~50 % of the batch size) and are in separate folder from the batch folders
*Successfully processed batches older than 14 days are deleted every day by another application that also produces log files about the successful/failed deletion
*For precaution let’s assume 5% of batches could fail to be processed correctly (however in obtained sample all batches were processed correctly)
**Those will stay on the server and will be processed every 6 months by admins when deleting backup

==Observation==
First observation was made to assess the data available and to decide about proper approach when designing the simulation.
Information gathered during observation:
*Each day an average of 17 batches were processed by the server with average size per batch of 24 MB
*The number of batches changes a lot and can’t be easily predicted so it will have to be taken into consideration
*Information about deleted batches can be found in database on the server

==Simulation environment==
MS Excel 2016
==Simulation method==
Monte Carlo

=Obtaining real data=
The data for simulation was extracted from a database which contains information about all the batches that were processed on the server during the last 65 working days. Total of 1124 batches were processed during those days. Important part of the database table needed for simulation is included in the MS Excel file.

=Derivation of probability distributions=
After the data was gathered and analyzed through a contingency table, graphs were made to display the average batch size (in bins with increment of 5000 KB) and the average batch count per day. Both those graphs are from the log-normal distribution and so the random values were generated based on those distributions for average batch size as well as the average batch count.

[[File:lognormaldistribution1.png|Number o batches in size bins (batch size range of 5000 KB, average)|center|500px|]]

[[File:lognormaldistribution2.png|Number of different batch count occurances (average)|center|500px|]]

=Simulation=
For the simulation 132 working days (6 months) were considered as the time before backup deletion and error fix-up takes place. For both average batch size and average batch count random values were generated from the log-normal distribution based on scaled mean (m) and standard deviation (s) of the original data set. 

Those random values were generated 132 times and then multiplied. After multiplication of those 2 values followed calculating the error and backup size and the cumulative size which was reduced each step starting at 10 steps (14 days for deletion of the oldest batch). Overall size after 6 months was used in excel data table to generate this simulation 1000 times.

=Results=
After generating 1000 simulations the AVG, highest and lowest space needed was calculated and is displayed in table below:

{| class="wikitable" style="margin: auto;"
|+1000 simulations results
|-
|
|In KB
|In MB
|In GB
|-
|'''AVG Space needed:'''
|35189448.7
|34364.7
|33.55927
|-
|'''Highest space needed:'''
|105577213
|103102.7
|100.6863
|-
|'''Lowest space needed:'''
|21607404.9
|21100.98
|20.60643
|}

Issue with the results is that the highest space needed changes a lot (because the batch size and count changes a lot as was mentioned at the beginning of the paper) even when running the simulation 1000 times. It had to be taken into consideration when deriving conclusions.

=Conclusion=
One option for the company when deciding how much space should be reserved for document processing based on the simulation would be to take into consideration the highest space needed from 1000 simulations which is nearly 101 GB. Second recommendation, when using this option, would be to monitor the server at least once a month as the highest value varies a lot and adjust the size if needed. Upside of this approach is that it requires less initial work. 
Due to high variance another approach for defining the space needed is to consider only the average space needed so the HDD would have “only” 34 GB free space starting each 6 months. However, when using this approach, if the HDD starts getting full, increasing the size automatically based on the last month when backup deletion took place is necessary. Upside of this solution is proper space utilization as most of the time big part of disk space would be unused if one considers only the highest size needed (based on the average space needed).

=Code=

The Excel file with simulation can be found here:
https://app.box.com/s/duj71rtgvf4g1u9gi011tcib2umnjdil

[[File:dolj04_Optimal size of HDD for virtual Digitization server.xlsx]]

Optimal size of HDD for virtual Digitization server

2019-01-24T13:58:28Z

Kadj02:

=Introduction=

Proper usage of server space and capacity is very important for companies these days as the volume of data gathered and produced is growing rapidly and is essential for proper operation of modern companies.
This simulation is designed to calculate optimal HDD size for a server which is used for processing documents and is based on real data obtained from a company production server.

=Problem definition=
The simulation is based on data gathered by a server application in database, observations of the server (mainly focused on batch count and their size) and additional information about the solution running on the server gathered from documentation:
*Processing takes place only on work days
*Every document scanned to the server is processed by a digitization application which creates batch that contains original scanned document, extracted data in XML files, log files, enhanced images and searchable PDF
*Application saves all important information about batches in database
*Backup images from scanning will stay on the server for 6 months (those are additional ~50 % of the batch size) and are in separate folder from the batch folders
*Successfully processed batches older than 14 days are deleted every day by another application that also produces log files about the successful/failed deletion
*For precaution let’s assume 5% of batches could fail to be processed correctly (however in obtained sample all batches were processed correctly)
**Those will stay on the server and will be processed every 6 months by admins when deleting backup

==Observation==
First observation was made to assess the data available and to decide about proper approach when designing the simulation.
Information gathered during observation:
*Each day an average of 17 batches were processed by the server with average size per batch of 24 MB
*The number of batches changes a lot and can’t be easily predicted so it will have to be taken into consideration
*Information about deleted batches can be found in database on the server

==Simulation environment==
MS Excel 2016
==Simulation method==
Monte Carlo

=Obtaining real data=
The data for simulation was extracted from a database which contains information about all the batches that were processed on the server during the last 65 working days. Total of 1124 batches were processed during those days. Important part of the database table needed for simulation is included in the MS Excel file.

=Derivation of probability distributions=
After the data was gathered and analyzed through a contingency table, graphs were made to display the average batch size (in bins with increment of 5000 KB) and the average batch count per day. Both those graphs are from the log-normal distribution and so the random values were generated based on those distributions for average batch size as well as the average batch count.

[[File:lognormaldistribution1.png|Number o batches in size bins (batch size range of 5000 KB, average)|center|500px|]]

[[File:lognormaldistribution2.png|Number of different batch count occurances (average)]]

=Simulation=
For the simulation 132 working days (6 months) were considered as the time before backup deletion and error fix-up takes place. For both average batch size and average batch count random values were generated from the log-normal distribution based on scaled mean (m) and standard deviation (s) of the original data set. 

Those random values were generated 132 times and then multiplied. After multiplication of those 2 values followed calculating the error and backup size and the cumulative size which was reduced each step starting at 10 steps (14 days for deletion of the oldest batch). Overall size after 6 months was used in excel data table to generate this simulation 1000 times.

=Results=
After generating 1000 simulations the AVG, highest and lowest space needed was calculated and is displayed in table below:

{| class="wikitable" style="margin: auto;"
|+1000 simulations results
|-
|
|In KB
|In MB
|In GB
|-
|'''AVG Space needed:'''
|35189448.7
|34364.7
|33.55927
|-
|'''Highest space needed:'''
|105577213
|103102.7
|100.6863
|-
|'''Lowest space needed:'''
|21607404.9
|21100.98
|20.60643
|}

Issue with the results is that the highest space needed changes a lot (because the batch size and count changes a lot as was mentioned at the beginning of the paper) even when running the simulation 1000 times. It had to be taken into consideration when deriving conclusions.

=Conclusion=
One option for the company when deciding how much space should be reserved for document processing based on the simulation would be to take into consideration the highest space needed from 1000 simulations which is nearly 101 GB. Second recommendation, when using this option, would be to monitor the server at least once a month as the highest value varies a lot and adjust the size if needed. Upside of this approach is that it requires less initial work. 
Due to high variance another approach for defining the space needed is to consider only the average space needed so the HDD would have “only” 34 GB free space starting each 6 months. However, when using this approach, if the HDD starts getting full, increasing the size automatically based on the last month when backup deletion took place is necessary. Upside of this solution is proper space utilization as most of the time big part of disk space would be unused if one considers only the highest size needed (based on the average space needed).

=Code=

The Excel file with simulation can be found here:
https://app.box.com/s/duj71rtgvf4g1u9gi011tcib2umnjdil

[[File:dolj04_Optimal size of HDD for virtual Digitization server.xlsx]]

File:Run down1.jpg

2019-01-24T13:57:06Z

Kadj02:

Slime mold

2019-01-24T13:56:43Z

Kadj02: /* Results */

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. [[File:run_down1.jpg|Successful rundown|center|500px|]] ( https://imgur.com/a/66qk95M ) There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. ( https://imgur.com/a/Jq9QHsH)
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. ( https://imgur.com/a/gkyCTwN - red are the dry ones, green are the healthy ones )

Sadly considering the nature of spreading of this mold there is an area given by the inner circle of the square-world, which formulates an impenetrable layer. There is a trigger for this in code, however in the random generated origins scenario there is a high possibility of triggering this very early in to simulation. ( https://imgur.com/a/AW1crvA )

==Numeric results==
Considering the nature of our simulation I decided to do extensive experimenting only with one point of origin in the center. Other alternatives were way too inconsistent considering so many depending variables were random generated. Together with the random motion of particles it was nearly impossible to derive any meaningful results.
For the conservative scenario there is threshold around 4000 units of mold-resource, where doesn’t really matter if there are any food present.
Everything above 4000 units of mold-resource is very depended on the number, strength and location of the food.
Above 25000 – 35000 units of mold-resource is almost certain that mold will consume all the food in the world.
And above 90000 there is for mold not really need for food to be present in the world whatsoever.
The effectiveness of the spores seems to be something below 20% - which means more than 80% spores die because they wander off the world’s edge.

=Conclusion=
The simulation were successful in replicating the pattern of the slime mold with the help of DLA algorithm. Unfortunately there were several issues with the simulation on the technical side as well as on the simulation side.
The possibilities with randomizing points of origins turned out to be not useful at all for drawing any meaningful conclusions. The world is very limited and therefore the patches has to be shrinked down by a lot. That leads in simulations with ending at some millionth tick. Adding that the number of particles in this world that needs to be redrawn every cycle leads to a very heavy computing power-hungry simulation.

=Code=
https://uloz.to/!Hf0bjuUH3dCS/slime-mold-nlogo

Serious Gaming - textbook text

2019-01-23T22:28:06Z

Kadj02:

=Introduction=
Serious Gaming as a term is often used by mainstream to describe professional gaming community, which is in fact incorrect. There is very clear distinction between playing games professionally to make money and looking on games as a learning tool. That could be packed together with simulation – army is using simulation for years to prepare its soldiers for specific combat situation.
Do you want to learn how to play guitar or drive a truck? -There is simulation even for that. Well with serious gaming we don’t mean only playing simulations or playing the game at all. You can learn – derive a deeper meaning from the game by looking at it, by maintaining it or by creating it.

=Economy=
So, in this topic I would like to choose this bird perspective and try to look at MMO’s and its ties with real world economy. MMO – Massive Multiplayer Online – that means a lot of people are playing at once in a shared world (for our purposes economic market) and it is connected at 24/7 basis. Every game in this genre has to deal with its economic challenges in a specific world and now it has become the best practice to use methods from the real world and its economy. The biggest a scariest challenge yet is inflation.

Let's start by defining "inflation" - when the buying power of a given amount of currency drops, we call that "inflation".
So, for example, a nickel buys a lot less in the United states today than it did in 1850.
As you probably know, whenever you print money in a real-world economy, you inflate the currency.
Print too much money and you hit hyperinflation - an economic state where the currency effectively becomes worthless.

=Hyperinflation=

MMOs suffer from a strange problem,
at least in a real world economic sense.
Everybody is printing money all the time.
For years, every massive multiplayer game
has struggled with this.
And as any old school MMO player will tell you,
the results were as devastating as they
often were hilarious. But of late, games
have stolen a very real world economic solution.

Economic balance in MMOs is one of the most complex things you can wrestle with as a designer.
And it offers a fascinating view into where real-world economic theory and the inherent strangeness of running an MMO collide.
But today, we're gonna dive into one of the most important issues that MMO economies face:
The tendency toward hyperinflation.
Pretty much any of you who have played an MMO for any length of time have seen this tendency in effect.
The value of a Gold piece in the game drops and drops as time passes.
In the first month after launch, you could buy great items for 20 gold pieces.
Fast forward to three years later, and those same items are costing ten thousand gold pieces in the auction house.

Imagine what this
would do to a real world economy.
Imagine if rather than your central bank
having the exclusive right to print
money and keeping careful tabs on how
much money is out there, everybody was
just printing money all the time.
You would hit hyperinflation pretty fast
The value of the currency would plummet
and the loaf of bread that costs five
dollars one day would cost 50 the next week.
And then 5,000. And then people
would just stop accepting money for
bread altogether. Your currency would be
effectively worthless. And that is
exactly what happens in most MMOs.
In Asheron's Call, the in-game currency
became so inflated that shards were used
as money. In Diablo 2, stones of Jordan
rapidly replaced gold. And in Gaia Online,
the currency became so worthless that
the company started offering to donate
two hundred and fifty dollars to charity
every time the players threw away 15
trillion gold. Players just abandoned the
designated currency and chose a
different, more restricted currency
because they could no longer trust the
initial game currency to retain any
value at all. And this has a devastating
impact on these games.
When you
paid for any of those items or services,
the money you paid with simply vanished,
which theoretically would have a
deflationary effect

But why does this hyperinflation happen in the first place, and how can we prevent it?

=Sinks=

In the real world, governments control how much money is printed in a given amount of time so that they can regulate how much currency enters the economy.
And thus control the rate of inflation to some degree.
But where does currency come from in an MMO?
Well, monsters.
Every time a monster spawns, you're effectively printing money.
Every time you kill a mob in an MMO, you either get money directly or you get loot that can be exchanged for money.
But to keep the game engaging for the players, these monsters have to respawn in a timely fashion with an amount of loot and currency similar to what they had last time they spawned.
If they didn't, you just end up with big empty zones with nothing to fight.
Or people feeling cheated when the first players to get to his own swipe all the good loot.
It would be a great way to kill your MMO in a hurry.
So over time, more and more currency is being added to the world as, in aggregate, the player base is killing and looting huge amounts of mobs.
This effectively devalues the currency and leads to runaway inflation creating the worthless currency scenario that I described before.
So what options do we have to regulate this virtual economy? -The standard answer is to find currency sinks.
Places where you can use game mechanics to take currency out of the world.

==Vendors==

The obvious go-to is your death mechanic.
Every time you die in World of Warcraft, your equipment takes damage.
Eventually you have to repair it, which costs money. And that money goes to a vendor, and not another player.
So you're giving money to an NPC without getting any resellable goods in return.
Effectively taking the full value of that repair out of the world economy.
It's a great design idea, but it's not gonna single-handedly solve your problem.
The trouble with death sinks is that it's almost impossible to make them effective enough by themselves without feeling onerous.

The only devs it seems come close to controlling inflation solely through death mechanics are the folks at CCP with Eve Online.
In that game, the economic cost of dying is so staggering, it becomes a strong tool to rein in inflation.
They also encourage large-scale player wars as a key element of the game.
These wars destroy so many goods, which then must be replaced, which helps to keep inflation in check.
But since death penalties alone usually aren't enough to prevent the hyperinflation incurred by player farming, what else do games do?

Well, first off, they use the buy and sell prices of vendors.
Note how most NPC vendors in these games only give you a very small percentage of an item's value when you try to sell it to them.
Where does that value difference go? Nowhere.
It falls out of the economy, effectively reducing the amount of currency in circulation.
Unfortunately, this technique isn't a cure-all for the problem either.
Because our NPC merchants aren't all that discriminating about what they'll buy.
In real life, a shopkeep would tell you, "No. Stop trying to sell me rusty knives."
"You've sold me thirty of them now. I don't want any more. Get out of here."
But nope, our NPCs are happy to pick up those tattered rat pelts all day long!
Rag, weeds, a handful of rocks...
Doesn't matter if they're worthless at the auction house; that NPC will buy as many as you can bring them.
This means that items which otherwise would have zero economic value now have some economic value due to our NPC vendors.
Which, in the end, often results in the sell function actually adding more currency to the economy than it removes.
This is doubly true when you introduce the concept of soulbound items.
Sure, it creates scarcity for those specific items,
but it also means the only place you can eventually offload them is with a vendor.
Which just floods more and more money into the economy.
If it were a regular item, it could at least get circulated among the playerbase forever as players kept selling it to each other, which is a currency neutral activity.

==Other means to regulate the economy==
But okay, what other options do we have?
Well, there's also consumables.
Potions, ammo, food and drink. All of these serve as ways to remove currency from the economy.
And games which make these systems crucial parts of play tend to do so that the designers can have a big lever to pull to stop runaway inflation when they need to.
Is inflation growing too fast? Well, create an expensive high-end consumable that all your players are gonna wanna burn through and you can level out that problem real quick.
Auction house fees are another common system.
Besides simply deterring players from putting up junk auctions all the time these fees serve to remove a small percentage of the cost of an item from the economy every time it circulates through the playerbase.
There's also services.
Have you ever wondered why you have to pay for fast travel, or why that griffin ride costs you money?
It's because it's another economic sink.
This can be anything from transportation, to fees for sending letters, to money paid to open up new bank slots.
All of these services take money from the player without returning a tangible good, thus effectively deleting that money from circulation.

Let's talk about some of the more inventive solutions that could be used.
First off, let's talk about this idea of tying currency to a consumable necessity.
Let's say, for example, that you put a high-end potion into your game for ten thousand gold that every raid player is gonna want every time they go raiding.
Now let's say that it's only purchasable from vendors.
And not only does this remove ten thousand gold from your economy every time a player swings one of these things but it also sets a baseline for the value of money.
Your currency may inflate, but by essentially backing it with another good - by saying that at any point, you can trade in ten thousand gold for this potion...
Your currency will never become worthless.
Or you could tie it to real-world currency. If players can trade your in-game currency for something with real-world value...
It'll inflate, but it'll always retain value.
In Eve Online, Plex serve this function.
Plex are game codes that can be used to pay the monthly subscription fee for the game, but they're also tradable on the in-game market.
And this means that the in-game currency will always have value, because it's tied directly to something with a real-world dollar value.
There are also taxation systems in games, which help to keep things regulated.
You wanna keep your guild for another month? Well, you better pay x amount of gold.
You wanna keep that farmland you bought? I guess you better pay the NPC lord a few hundred guilders before the week is out.
It's an effective option, although it's really hard to manage without making it feel burdensome to the player.
Lastly, there's the idea of permanent purchasable upgrades for a character.
We do already use this to a limited degree.
Have you ever wondered why this trainer who wants to guide you through life or prepare you to save the world isn't gonna teach you that new kick until you fork over four platinum?
It's to get that money out of the game.
The problem is that this often stops at the level cap, when you run out of stuff to learn.
Which is unfortunate, because that's the place where it would actually be most effective.
There is an alternative, though: premium endgame trainers.
Have you already maxed out your level?
Well, here's a special trainer who will increase any stat you want by one point, for 40,000 experience points and 10,000 gold.
The great thing about this is that it can be an exponential system, which causes the high-end players to just drain money out of the economy.
Which is good, because those players are usually the biggest generators of inflationary influxes of cash.

=Reserve currency=

It seems like
designers have discovered another solution.
A reserve currency. In the real
world, almost every nation holds onto a
bunch of currency from other countries
to serve as a reserve currency.
This reserve currency is used for
international transactions, but far more
importantly to us, it's used to anchor
the local currency. Because, after all, if
you have 500 billion dollars in the bank
and you tell everybody that they can
trade 50 of your currency for one u.s.
dollar
well then the least your currency is
worth is 2 cents. It can't go below that
so long as you've got some of your
reserve currency left. If your currency
starts to inflate, then people start to
trade in your local money for the
reserve currency, effectively creating a
floor for what your currency is worth so
long as you still have a supply of the
reserve currency. So how does this work
in MMOs? Well of late, many MMOs have
started to allow players to buy things
of real-world value with in-game
currency, like Plex in EVE Online.
Many of the free-to-play MMOs have gone one step
even further and let players buy their
microtransaction currency -- the currency
that has to be bought with real money --
from other players for currency earned
in game. By tying the in-game currency to
real world currency, which has real value,
the in-game currency now can't lose all
of its value. But that alone didn't end
up being enough to prevent
hyperinflation in a lot of these games,
so two other aspects, somewhat lifted
from how real world reserve currencies work,
were put into place in order to overcome
the infinite money printing that MMOs
naturally engage in. The first is
illiquidity. In the real world, reserve
currencies can't really be traded among
the local populace. Like if you go to
China, even though the Chinese keep huge
amounts of US dollars as reserve
currency, you can't really simply trade
US dollars for things on the street.
You usually need to convert your money into
yuan first. And while clearly this is
not a hundred percent true in the real
world because the real world basically
breaks every rule at some point, you can
make it a hundred percent true in games
because you set the rules of that world.
You can prevent players from trading the
purchased currency. Players can convert
their earned currency to purchased
currency.

Serious Gaming - textbook text

2019-01-23T22:02:05Z

Kadj02: Blanked the page

Serious Gaming - textbook text

2019-01-23T22:01:43Z

Kadj02: Created page with "=Introduction= =Economy= Let's start by defining "inflation" - when the buying power of a given amount of currency drops, we call that "inflation". So, for example, a nickel..."

=Introduction=

=Economy=
Let's start by defining "inflation" - when the buying power of a given amount of currency drops, we call that "inflation".
So, for example, a nickel buys a lot less in the United states today than it did in 1850.
As you probably know, whenever you print money in a real-world economy, you inflate the currency.
Print too much money and you hit hyperinflation - an economic state where the currency effectively becomes worthless.

=Connection between real economy in games=

=Hyperinflation=
Economic balance in MMOs is one of the most complex things you can wrestle with as a designer.
And it offers a fascinating view into where real-world economic theory and the inherent strangeness of running an MMO collide.
But today, we're gonna dive into one of the most important issues that MMO economies face:
The tendency toward hyperinflation.
Pretty much any of you who have played an MMO for any length of time have seen this tendency in effect.
The value of a Gold piece in the game drops and drops as time passes.
In the first month after launch, you could buy great items for 20 gold pieces.
Fast forward to three years later, and those same items are costing ten thousand gold pieces in the auction house.
This is why players eventually improvise by adopting alternate currencies such as Stones of Jordan in Diablo 2, or Shards in Asheron's Call.
But why does this hyperinflation happen in the first place, and how can we prevent it?

=Sinks=

In the real world, governments control how much money is printed in a given amount of time so that they can regulate how much currency enters the economy.
And thus control the rate of inflation to some degree.
But where does currency come from in an MMO?
Well, monsters.
Every time a monster spawns, you're effectively printing money.
Every time you kill a mob in an MMO, you either get money directly or you get loot that can be exchanged for money.
But to keep the game engaging for the players, these monsters have to respawn in a timely fashion with an amount of loot and currency similar to what they had last time they spawned.
If they didn't, you just end up with big empty zones with nothing to fight.
Or people feeling cheated when the first players to get to his own swipe all the good loot.
It would be a great way to kill your MMO in a hurry.
So over time, more and more currency is being added to the world as, in aggregate, the player base is killing and looting huge amounts of mobs.
This effectively devalues the currency and leads to runaway inflation creating the worthless currency scenario that I described before.
So what options do we have to regulate this virtual economy? -The standard answer is to find currency sinks.
Places where you can use game mechanics to take currency out of the world.

==Vendors==

The obvious go-to is your death mechanic.
Every time you die in World of Warcraft, your equipment takes damage.
Eventually you have to repair it, which costs money. And that money goes to a vendor, and not another player.
So you're giving money to an NPC without getting any resellable goods in return.
Effectively taking the full value of that repair out of the world economy.
It's a great design idea, but it's not gonna single-handedly solve your problem.
The trouble with death sinks is that it's almost impossible to make them effective enough by themselves without feeling onerous.

The only devs it seems come close to controlling inflation solely through death mechanics are the folks at CCP with Eve Online.
In that game, the economic cost of dying is so staggering, it becomes a strong tool to rein in inflation.
They also encourage large-scale player wars as a key element of the game.
These wars destroy so many goods, which then must be replaced, which helps to keep inflation in check.
But since death penalties alone usually aren't enough to prevent the hyperinflation incurred by player farming, what else do games do?

Well, first off, they use the buy and sell prices of vendors.
Note how most NPC vendors in these games only give you a very small percentage of an item's value when you try to sell it to them.
Where does that value difference go? Nowhere.
It falls out of the economy, effectively reducing the amount of currency in circulation.
Unfortunately, this technique isn't a cure-all for the problem either.
Because our NPC merchants aren't all that discriminating about what they'll buy.
In real life, a shopkeep would tell you, "No. Stop trying to sell me rusty knives."
"You've sold me thirty of them now. I don't want any more. Get out of here."
But nope, our NPCs are happy to pick up those tattered rat pelts all day long!
Rag, weeds, a handful of rocks...
Doesn't matter if they're worthless at the auction house; that NPC will buy as many as you can bring them.
This means that items which otherwise would have zero economic value now have some economic value due to our NPC vendors.
Which, in the end, often results in the sell function actually adding more currency to the economy than it removes.
This is doubly true when you introduce the concept of soulbound items.
Sure, it creates scarcity for those specific items,
but it also means the only place you can eventually offload them is with a vendor.
Which just floods more and more money into the economy.
If it were a regular item, it could at least get circulated among the playerbase forever as players kept selling it to each other, which is a currency neutral activity.

==Other means to regulate the economy==
But okay, what other options do we have?
Well, there's also consumables.
Potions, ammo, food and drink. All of these serve as ways to remove currency from the economy.
And games which make these systems crucial parts of play tend to do so that the designers can have a big lever to pull to stop runaway inflation when they need to.
Is inflation growing too fast? Well, create an expensive high-end consumable that all your players are gonna wanna burn through and you can level out that problem real quick.
Auction house fees are another common system.
Besides simply deterring players from putting up junk auctions all the time these fees serve to remove a small percentage of the cost of an item from the economy every time it circulates through the playerbase.
There's also services.
Have you ever wondered why you have to pay for fast travel, or why that griffin ride costs you money?
It's because it's another economic sink.
This can be anything from transportation, to fees for sending letters, to money paid to open up new bank slots.
All of these services take money from the player without returning a tangible good, thus effectively deleting that money from circulation.

Let's talk about some of the more inventive solutions that could be used.
First off, let's talk about this idea of tying currency to a consumable necessity.
Let's say, for example, that you put a high-end potion into your game for ten thousand gold that every raid player is gonna want every time they go raiding.
Now let's say that it's only purchasable from vendors.
And not only does this remove ten thousand gold from your economy every time a player swings one of these things but it also sets a baseline for the value of money.
Your currency may inflate, but by essentially backing it with another good - by saying that at any point, you can trade in ten thousand gold for this potion...
Your currency will never become worthless.
Or you could tie it to real-world currency. If players can trade your in-game currency for something with real-world value...
It'll inflate, but it'll always retain value.
In Eve Online, Plex serve this function.
Plex are game codes that can be used to pay the monthly subscription fee for the game, but they're also tradable on the in-game market.
And this means that the in-game currency will always have value, because it's tied directly to something with a real-world dollar value.
There are also taxation systems in games, which help to keep things regulated.
You wanna keep your guild for another month? Well, you better pay x amount of gold.
You wanna keep that farmland you bought? I guess you better pay the NPC lord a few hundred guilders before the week is out.
It's an effective option, although it's really hard to manage without making it feel burdensome to the player.
Lastly, there's the idea of permanent purchasable upgrades for a character.
We do already use this to a limited degree.
Have you ever wondered why this trainer who wants to guide you through life or prepare you to save the world isn't gonna teach you that new kick until you fork over four platinum?
It's to get that money out of the game.
The problem is that this often stops at the level cap, when you run out of stuff to learn.
Which is unfortunate, because that's the place where it would actually be most effective.
There is an alternative, though: premium endgame trainers.
Have you already maxed out your level?
Well, here's a special trainer who will increase any stat you want by one point, for 40,000 experience points and 10,000 gold.
The great thing about this is that it can be an exponential system, which causes the high-end players to just drain money out of the economy.
Which is good, because those players are usually the biggest generators of inflationary influxes of cash.

WS 2018/2019

2019-01-23T21:22:29Z

Kadj02:

Semestral papers from winter term 2018/2019. Please, put here links to the pages with your paper. First you need to have your [[Assignments WS 2018/2019|assignment approved]]

==Simulations==

--[[User:xvegm00|xvegm00]] [[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 22:13, 8 January 2019 (CET) [[Simulation of semi-intelligent algae]]

-- Jan Doležálek [[User:Dolj04|Dolj04]] ([[User talk:Dolj04|talk]]) 16:50, 18 January 2019 (CET) [[Optimal size of HDD for virtual Digitization server]]

-- Jiří Korčák [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 11:09, 19 January 2019 (CET) [[Vacuum cleaner]]

-- Jan Mandík [[User:Manj01|Manj01]] ([[User talk:Manj01|talk]]) 14:46, 19 January 2019 (CET) [[Ticket Solving Process at a Small IT dev Company]]

-- [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 18:43, 19 January 2019 (CET) [[evacuation from burning building]]

-- [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 12:11, 20 January 2019 (CET) [[Medieval Battle Simulation]]

-- [[User:Qnesa01|Qnesa01]] ([User talk:Qnesa01|talk]]) 16:19, 20 January 2019 (CET) [[Argentinska Intersection]]

-- Jan Pippal (xpipj04) [[User:Janpippal|Janpippal]] 16:41, 20 January 2019 (CET) [[You are what you eat]]

-- [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) 23:19, 20 January 2019 (CET) [[Slime mold]]

-- [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 01:38, 21 January 2019 (CET) [[Simulation of north korea migration]]

==Papers==
-- [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 20:43, 12 January 2019 (CET) [https://en.wikipedia.org/wiki/Data_flow_diagram Complete redo of DFD wikipedia]~

-- [[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 10:44, 17 January 2019 (CET) [[http://www.simulace.info/index.php/Multi-agent_systems Multi-agent systems]]

-- Jan Pippal (xpipj04) [[User:Janpippal|Janpippal]] 4:48, 20 January 2019 (CET) [https://en.wikipedia.org/wiki/Draft:MMABP MMABP in English]

-- [[User:Qnesa01|Qnesa01]] ([User talk:Qnesa01|talk]]) 17:19, 20 January 2019 (CET) [[Limits to Growth_ver2]]

-- Tomáš Smysl (xsmyt00) [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 22:36, 20 January 2019 (CET) [[https://en.wikipedia.org/wiki/ArchiMate ArchiMate wiki]] Note: I had some issues with the Wikipedia image upload - they did not approve my images. [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 13:53, 23 January 2019 (CET) EDIT: Solved.

-- Jan Doležálek [[User:Dolj04|Dolj04]] ([[User talk:Dolj04|talk]]) 11:09, 21 January 2019 (CET) [[http://www.simulace.info/index.php/Variance_reduction Variance reduction]]

-- Jan Mandík [[User:Manj01|Manj01]] ([[User talk:Manj01|talk]]) 21:52, 21 January 2019 (CET) [[Vickrey%27s_auction]]

-- [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) 22:21, 23 January 2019 (CET) [[Serious Gaming - textbook text]]

WS 2018/2019

2019-01-23T21:21:35Z

Kadj02:

Slime mold

2019-01-20T22:50:57Z

Kadj02:

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. ( https://imgur.com/a/66qk95M ) There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. ( https://imgur.com/a/Jq9QHsH)
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. ( https://imgur.com/a/gkyCTwN - red are the dry ones, green are the healthy ones )

Sadly considering the nature of spreading of this mold there is an area given by the inner circle of the square-world, which formulates an impenetrable layer. There is a trigger for this in code, however in the random generated origins scenario there is a high possibility of triggering this very early in to simulation. ( https://imgur.com/a/AW1crvA )

==Numeric results==
Considering the nature of our simulation I decided to do extensive experimenting only with one point of origin in the center. Other alternatives were way too inconsistent considering so many depending variables were random generated. Together with the random motion of particles it was nearly impossible to derive any meaningful results.
For the conservative scenario there is threshold around 4000 units of mold-resource, where doesn’t really matter if there are any food present.
Everything above 4000 units of mold-resource is very depended on the number, strength and location of the food.
Above 25000 – 35000 units of mold-resource is almost certain that mold will consume all the food in the world.
And above 90000 there is for mold not really need for food to be present in the world whatsoever.
The effectiveness of the spores seems to be something below 20% - which means more than 80% spores die because they wander off the world’s edge.

=Conclusion=
The simulation were successful in replicating the pattern of the slime mold with the help of DLA algorithm. Unfortunately there were several issues with the simulation on the technical side as well as on the simulation side.
The possibilities with randomizing points of origins turned out to be not useful at all for drawing any meaningful conclusions. The world is very limited and therefore the patches has to be shrinked down by a lot. That leads in simulations with ending at some millionth tick. Adding that the number of particles in this world that needs to be redrawn every cycle leads to a very heavy computing power-hungry simulation.

=Code=
https://uloz.to/!Hf0bjuUH3dCS/slime-mold-nlogo

Slime mold

2019-01-20T22:42:27Z

Kadj02: /* Results */

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. ( https://imgur.com/a/66qk95M ) There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. ( https://imgur.com/a/Jq9QHsH)
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. ( https://imgur.com/a/gkyCTwN - red are the dry ones, green are the healthy ones )

Sadly considering the nature of spreading of this mold there is an area given by the inner circle of the square-world, which formulates an impenetrable layer. There is a trigger for this in code, however in the random generated origins scenario there is a high possibility of triggering this very early in to simulation. ( https://imgur.com/a/AW1crvA )

==Numeric results==
Considering the nature of our simulation I decided to do extensive experimenting only with one point of origin in the center. Other alternatives were way too inconsistent considering so many depending variables were random generated. Together with the random motion of particles it was nearly impossible to derive any meaningful results.
For the conservative scenario there is threshold around 4000 units of mold-resource, where doesn’t really matter if there are any food present.
Everything above 4000 units of mold-resource is very depended on the number, strength and location of the food.
Above 25000 – 35000 units of mold-resource is almost certain that mold will consume all the food in the world.
And above 90000 there is for mold not really need for food to be present in the world whatsoever.
The effectiveness of the spores seems to be something below 20% - which means more than 80% spores die because they wander off the world’s edge.

Slime mold

2019-01-20T22:42:18Z

Kadj02: /* Results */

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. ( https://imgur.com/a/66qk95M ) There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. ( https://imgur.com/a/Jq9QHsH)
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. ( https://imgur.com/a/gkyCTwN - red are the dry ones, green are the healthy ones )

Sadly considering the nature of spreading of this mold there is an area given by the inner circle of the square-world, which formulates an impenetrable layer. There is a trigger for this in code, however in the random generated origins scenario there is a high possibility of triggering this very early in to simulation. ( https://imgur.com/a/AW1crvA )

==Numeric results
Considering the nature of our simulation I decided to do extensive experimenting only with one point of origin in the center. Other alternatives were way too inconsistent considering so many depending variables were random generated. Together with the random motion of particles it was nearly impossible to derive any meaningful results.
For the conservative scenario there is threshold around 4000 units of mold-resource, where doesn’t really matter if there are any food present.
Everything above 4000 units of mold-resource is very depended on the number, strength and location of the food.
Above 25000 – 35000 units of mold-resource is almost certain that mold will consume all the food in the world.
And above 90000 there is for mold not really need for food to be present in the world whatsoever.
The effectiveness of the spores seems to be something below 20% - which means more than 80% spores die because they wander off the world’s edge.

Slime mold

2019-01-20T22:33:16Z

Kadj02: /* Results */

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. ( https://imgur.com/a/66qk95M ) There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. ( https://imgur.com/a/Jq9QHsH)
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. ( https://imgur.com/a/gkyCTwN - red are the dry ones, green are the healthy ones )

Sadly considering the nature of spreading of this mold there is an area given by the inner circle of the square-world, which formulates an impenetrable layer. There is a trigger for this in code, however in the random generated origins scenario there is a high possibility of triggering this very early in to simulation. ( https://imgur.com/a/AW1crvA )

Slime mold

2019-01-20T22:29:13Z

Kadj02: /* Results */

=Introduction=
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular, light can repel the slime mold and be a factor in triggering spore growth.
The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path. Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

=Problem definition=
The biggest challenge of this simulation is the correct format of the pattern movement when the mold spreads. The ability to find most effective route while keep this randomized movement pattern is the alfa and omega of the whole simulation. The movement itself is useless without considering the mold is also living organism and as every living organism its main purpose is to survive. Therefore there has to be a resource in place to be capable of deciding when the mold actually dies. This resource is of course possible to replenish by some interaction with the environment – and that’s surviving in a nutshell.
In order to correctly replicate the well know pattern movement from nature the agents have to be compliant with two vital rules. Diffusion-limited aggregation describes how replicate such pattern with particles moving corresponding to a Brownian motion.

==DLA-alorithm==
A DLA consists of particles that attach to each other. How they attach is described here. First of all, we start with a complete empty space and put one particle somewhere in it. Now, a second particle is 'fired' at an infinitely distance away from this particle. This new particle keeps moving randomly in the empty space until it collides with the already placed particle. At this moment, the particles attach to each other and are settled. Now a third particle is fired likewise, and the same procedure repeats itself over and over.
==Brownian motion==
If a number of particles subject to Brownian motion are present in a given medium and there is no preferred direction for the random oscillations, then over a period of time the particles will tend to be spread evenly throughout the medium. Thus, if A and B are two adjacent regions and, at time t, A contains twice as many particles as B, at that instant the probability of a particle’s leaving A to enter B is twice as great as the probability that a particle will leave B to enter A.

==Software==
Simulation is created using Netlogo 6.0.2.

=Model=
==Agents==
Agents are spawned and placed on the edge of the world facing in to the center. Every tick they move unpredictably and if they reach to the edge they will deleted. In this instance we call the agents spores and they only purpose is to die. One way I already mentioned, the second is to bump to a slime mold cell. The creation of new spores depends on current number of spores in the simulation (to prevent from clustering) and on the resources of the mold in this world. Every unit of resource is one agent which is capable of creating one slime mold cell. Their visibility can be switch on and off by user. Spores are created from resource called “endurance of mold” every cycle up to number defined by “spores by cycle”.
==Slime mold==
The yellow pixels represent the slime mold itself. Those cell are static and are waiting for incoming spores to help them find food (spread). Current number of mold cell are displayed in the plot “Number of mold cells” with additional exact number. The origin point can be put directly in to the center of the world. Also the number of the origin points can be up to 5 and they are going to be generated in random points in defined radius.
==Food==
The food is represented in this simulation as a red pixels. The amount of these pixels can be shifted up to 50 by user and are generated randomly in defined radius around circle. The amount of gained resources can be also adjusted up to 20000 with slider named “power of food”. Once agent (spore) connects the slime mold with a food pixel the mold gains that defined amount of resources immediately.

=Method=
In every tick agents move forward in a random matter and if there is a collision with a mold cell, they transform itself in that cell also - spreading in to space. The randomized spawning was a little bit tricky without the ability to correctly generating signed integers. To workaround this I came up with:

ifelse random 1 = 1 [set originX random-float 80] [set originX random-float -80] ;;true random signed int
ifelse random 1 = 1 [set originY random-float 80] [set originY random-float -80] ;;true random signed int

In a setup we set the patch size to a much smaller number, otherwise the patterns would not have been so visible. After setting all user-depended inputs there is endless cycle of wandering spores waiting to be terminated.

=Results=
The pattern replicating was u huge success. ( https://imgur.com/a/66qk95M ) There are really obvious similarities between our simulation and the video showcasing the spreading of the mold. Also the food which is founded by the mold is very clear on the plot of the resources. ( https://imgur.com/a/Jq9QHsH)
One very interesting founding is that if there are 4 or 5 points of origins, there is a high probability of drying out one or two branches and the other remaining branches wraps around them. ( https://imgur.com/a/gkyCTwN )

Slime mold

2019-01-20T22:23:01Z

Kadj02: /* Method */

Slime mold

2019-01-20T22:21:52Z

Kadj02: /* Model */

Slime mold

2019-01-20T22:21:35Z

Kadj02: /* Problem definition */

Slime mold

2019-01-20T22:21:10Z

Kadj02: Created page with "=Introduction= Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas, such as decaying leaves and logs. Like slime molds..."

WS 2018/2019

2019-01-20T22:19:50Z

Kadj02:

Semestral papers from winter term 2018/2019. Please, put here links to the pages with your paper. First you need to have your [[Assignments WS 2018/2019|assignment approved]]

==Simulations==

--[[User:xvegm00|xvegm00]] [[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 22:13, 8 January 2019 (CET) [[Simulation of semi-intelligent algae]]

-- Jan Doležálek [[User:Dolj04|Dolj04]] ([[User talk:Dolj04|talk]]) 16:50, 18 January 2019 (CET) [[Optimal size of HDD for virtual Digitization server]]

-- Jiří Korčák [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 11:09, 19 January 2019 (CET) [[Vacuum cleaner]]

-- Jan Mandík [[User:Manj01|Manj01]] ([[User talk:Manj01|talk]]) 14:46, 19 January 2019 (CET) [[Ticket Solving Process at a Small IT dev Company]]

-- [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 18:43, 19 January 2019 (CET) [[evacuation from burning building]]

-- [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 12:11, 20 January 2019 (CET) [[Medieval Battle Simulation]]

-- [[User:Qnesa01|Qnesa01]] ([User talk:Qnesa01|talk]]) 16:19, 20 January 2019 (CET) [[Argentinska Intersection]]

-- Jan Pippal (xpipj04) [[User:Janpippal|Janpippal]] 16:41, 20 January 2019 (CET) [[You are what you eat]]

-- [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) 23:19, 20 January 2019 (CET) [[Slime mold]]

==Papers==
-- [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 20:43, 12 January 2019 (CET) [https://en.wikipedia.org/wiki/Data_flow_diagram Complete redo of DFD wikipedia]~

-- [[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 10:44, 17 January 2019 (CET) [[http://www.simulace.info/index.php/Multi-agent_systems Multi-agent systems]]

-- Jan Pippal (xpipj04) [[User:Janpippal|Janpippal]] 4:48, 20 January 2019 (CET) [https://en.wikipedia.org/wiki/Draft:MMABP MMABP in English]

-- [[User:Qnesa01|Qnesa01]] ([User talk:Qnesa01|talk]]) 17:19, 20 January 2019 (CET) [[Limits to Growth_ver2]] (WIP)

-- Tomáš Smysl (xsmyt00) [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 22:36, 20 January 2019 (CET) [[https://en.wikipedia.org/wiki/ArchiMate ArchiMate wiki]] Note: I had some issues with the Wikipedia image upload - they did not approve my images. So the visual part of the Paper is missing examples of models that would ilustrate the text, which is quite unfortunate considering the topic is a visual modeling tool. I hope it can be solved later on. I even redrew some of the models so there would not be an issue with rights.

Assignments WS 2018/2019

2019-01-07T14:26:45Z

Kadj02: /* Simulation proposal Kadj02 (talk) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) */

{{Ambox
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Please, put here your assignments. Do not forget to sign them. You can use <nowiki>~~~~</nowiki> (four tildas) for an automatic signature. Use Show preview in order to check the result before your final sumbition.
</div>
}}

{{Ambox
| text = <div>
Please, strive to formulate your assignment carefully. We expect an adequate effort to formulate the assignment as it is your semestral paper. Do not forget that your main goal is a research paper. It means your simulation model must generate the results that are specific, measurable and verifiable. Think twice how you will develop your model, which entities you will use, draw a model diagram, consider what you will measure. No sooner than when you have a good idea about the model, submit your assignment. And of course, read [[How to deal with the simulation assignment|How to deal with the simulation assignment]].
</div>
}}

{{Ambox
| text = <div>
Topics on gambling, cards, etc. are not welcome.
</div>
}}

{{Ambox
| type = content
| text = <div>
In order to avoid possible confusion, please, check if you have added '''approved''' in bold somewhere in our comment under your submission. If there is no '''approved''', it means the assignment was not approved yet.
</div>
}}

----

== Simulation proposal ([[Xvegm00|Xvegm00]]) Simulation of semi-intelligent algae (Not approved yet)==

This Netlogo simulation aims to copy the behaviour of a symbiotic organism called physarum polycephalum. Physarum is actually a single cell organism, but when two or more cells meet, their membranes merge together and they work together to efficiently gather nutrition and multiply.
This simulation should mimic the spread and path creation of the algae, as well as its ability to solve the shortest path problem.
Video about physarum: [https://www.youtube.com/embed/HyzT5b0tNtk]

The algae should work in two modes: food search and optimisation. The food search part involves the algae spreading in a radial pattern, until it finds a foodsource. When it succeeds, it should optimise its pathways to allow for fastest nutrient transport.
The goal is for the algae to be able to find the shortest path to food source (and optimize - destroy/recontruct exisiting pathways). It should be able to work around obstacles as well. A test of function could be for the algae to find a path through a wall with three holes and to choose the proper hole (with shortest path).

Initial plan
There is an initial node, where the algae begins and from which it spreads.
Food is randomly distributed across the area, defined be a patch of certain color.
Algae spreads as agents, leaving behind patches as temporary algae. Temporary algae have a time to live, a timeout. When foodsource is found, nutrients travel as agents back to to initial node. When nutrients visit an algae patch, they reset its timeout. Thus, only the algae which has nutrients travelling on it can survive. With a properly applied randonmness, for the travel of nutrients as well as the agents, this should optimise the pathways.

''Assignment''
Title: Simulation of semi-intelligent algae

Course: 4IT496 Simulace systémů (v angličtině) (WS 2018/2019)

Author: Bc. Martin Vegner

Model type: Multiagent

Modeling tool: NetLogo

[[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 13:23, 30 December 2018 (CET)

: Generally, it could be done, but it is necessary to elaborate this assignment into greater detail. How you will measure the results? How you can say if it was successful or not? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 02:21, 31 December 2018 (CET)
:: Asiggnment updated. Please revise. [[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 14:33, 31 December 2018 (CET)
::: Ok, now I understand it better, how the simulation works, and it is fine. The only questionmark is still the results. What is the problem you study? What is the question you solve? How do you verify, your simulation solved the problem? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:30, 31 December 2018 (CET)
:::: It solves the travelling salesmen problem, which is algoritmically NP complete problem. However, it is solved through agents, which incorporates emergent intelligence, through orderly behaviour of agents. It explains how a group of algae, without any neurons or thinking organs, solves difficult problems. It shows, that there is a simple and low requirement solution to the problem. It offers a different solution to calculating the path, instead a simulation can be used to plan roads between cities for example. It can be verified, as i suggested in the assignment, by making it find the shortest path arround obstacles. It even adapts to changes in the topology.[[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 23:26, 1 January 2019 (CET)

== Simulation proposal ([[xkorj58|xkorj58]]) Find the thief (Not approved yet)==

This simulation should be created as a space search. There shall be two types of agents - first ones, police officers looking for a thief. Second a thief (moveable or imoveable) which is about to be found. Room itself could have obstacles. Police officers will have a vision, can have memory, could be various number of them and level of shared information about searched fields.

''Description''

Environment will have certain number of walls through which agent (police officer) can't see. In this environment will be thief to find (moving or stable). It will be a closed environment (walled from all sides), for the agent information about the environment will be inaccessible, he will not know, where the walls are and how many of them there is. It will be deterministic - every step of one of agents will have just one effect - on agent itself. This leads to a static environment - agents will be the only moving things in it. As the environment is closed it will have certain number of possible actions. Thus it will be discrete and dimensional.

Agents will at first randomly run through the space. It will have a vision (few patches in front of him). It will also save information about what he saw, therefore he will know where should he go to explore unseen locations. From this comes his intelligence. In situation with more agents, they will share this information about space and create for themselves a map of the environment (already searched patches).

''Assignment''

Title: Find the thief

Course: 4IT496 Simulace systémů (v angličtině) (WS 2018/2019)

Author: Bc. Jiří Korčák

Model type: Multiagent

Modeling tool: NetLogo

[[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 16:03, 17 December 2018 (CET)

: Sorry, but I don't understand what is this simulation good for. What meaningful problem do you solve? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:44, 31 December 2018 (CET)
::The problem should be about how memory, number of police officers and shared informations influence searching for a thief. It could have applications for AI in computer games (thats where you meet agents like this ones) or even in real life - most important thing when looking for something is: ... (when there is 20 of us looking for something, memory and shared information is not that important, etc.). [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 10:36, 31 December 2018 (CET)
::: The assignment is too brief. For the real situation, you definitely need stated where do you find relevant data to be able setting the parameters of the simulation. If you want to develop an intelligent agent for using in e.g. computer games, I am fine with that, but you need to define the environment, you need to define, how the agent should exactly behave, how his intelligence works, etc.
::: Please, choose one of the approaches (I would recommend the second one), and describe the problem really in detail. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:35, 31 December 2018 (CET)
:::: I think, I'll pick the second one. Up in describtion I tried to define the environment and the agents intelligence. I'm not sure if it's complex enough. What do you recommend in this situation and simulation to upgrade? Escpecially about the agents (officers and thiefs). Thanks for your answer. [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 02:48, 2 January 2019 (CET)

== Simulation proposal (dolj04) ==

Topic/goal: '''Optimal size of HDD for virtual Digitization server'''

Definition of the problem: 
- each day an average of 47 batches of documents is being processed by the server with average size per batch of 32 MB (calculated from customers server) 
- the number of batches changes a lot and cant be easily predicted so it will have to be taken into consideration (from sample: lowest number of batches scanned in a day is 13, the highest is 134) 
- the average size is not changing that much 
- (batch contains original scanned documents, extracted data in XML files, log files, enhanced images and searchable PDF) 
- backup images from scanning will stay on the server for 6 months (those are ''additional'' ~50 % of the batch size) 
- successfully processed batches older than 14 days are deleted every day 
- for precaution lets say around 5% of batches wont be processed correctly 
- those will stay on the server and will be processed every month by admins 

Simulation environment: Vensim

:: on what data you will base the simulation? I do not see any causal loops in the issue you are trying to solve, using Vesim does not make much sense then- this topic suits the Monte Carlo if you have the data to derive the parameters from. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:38, 18 December 2018 (CET)

:::: I would like to take the data at work as I have access to production server which is used by one of our customers for digitization and I will use Monte Carlo as you suggested.

::::::OK.'''Approved'''. Make sure that the derivation of probability distributions out of the real data for generating the random values is also part of your paper.[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 08:38, 20 December 2018 (CET)

== Simulation proposal (svem02 [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 18:42, 18 December 2018 (CET)) ==

Topic: '''likelihood of infection with flu'''

Definition of the problem: 
- everyone has a certain probability of getting sick with a flu, this model calculates the probability based on the people you are in contact with (two types of people, infected, not infected). Other variables and levels are available (e.g. infestation, total population 

Simulation environment: Vensim

:: on what data you would set up the simulation? how would you simulate the individual people and their connection in Vensim? (in my opinon this topic fits multiagent simulation) [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:30, 18 December 2018 (CET)

:::: I would base the simulation on how much one person interacts with others, depending on this variable the person would have some probability of getting sick thus the number of ill people would increase thus the probability of him getting sick would be higher and higher. The variable infestation would represent how much the illness is easily transimited to other people. [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 14:04, 19 December 2018 (CET)
:::::: I do not see it as simulation - not much of randomness, no causal feedback loops and pretty obvious result (the longer the simulation would run, the more sick people or that one gets sick) with no practical use. Not to mention, there is no data to derive the equations needed. Either reformulate it for the Netlogo so that it has some useful results based on some real data, or try something else. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 14:27, 19 December 2018 (CET)
:::::::: Ok, I will try something else. New proposal at the bottom of the page [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 16:46, 19 December 2018 (CET)
----

== Simulation proposal ([[User:xkaij00|xkaij00]] ([[User talk:xkaij00|talk]]) 21:20, 18 December 2018 (CET)) ==

Topic: '''Social and economical effects of reunification of North & South Korea''' 
'''Definition of the problem:''' 
Let's hope one day South and North Korea will be reunited. That would mean a big fluctuation of people between the two separated states: 
- North Koreans will migrate to South Korea area, look for flats, try to get jobs and receive welfare. 
- South Koreans will invest in North Korea area and create jobs and factories there. 
''I would like to simulate:'' 
- What will be the population ratio of the two areas per square meter. 
- How many North Koreans will move to South Korea area after the reunification and how many of them will be on welfare and how much that will cost the new reunited country. 
- How much will the suicide rate change in Korea after the reunification since it's a known fact that defected North Koreans have a high suicide rate due to the fact they have difficulties to adjust to the new lifestyle and process propaganda-free information. 
- What will be the housing situation after the reunification. 
- How will the GDP of the new country possibly develop. 
- Possibly how much money will be needed from international help. 
'''Simulation environment:''' NetLogo

----
: I must say it is a really interesting topic, but I am afraid it is a bit too ambitious. Please, if you are interested in this topic, elaborate in detail, how you would solve it. What agents would you use, what parameters, how the simulation would look like, on what data it should be based (and where you get them). And perhaps focus on fewer goals. To be honest, I am still not sure if this is doable, because of the need for extensive research. But, try to think about it yourself. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 19:26, 19 December 2018 (CET)
----
:: Thank you for the feedback - I tried to break down and simplify the simulation:

:: '''Agents:'''

:: - North Koreans (0-14 years)
:: - North Koreans (15-24 years)
:: - North Koreans (25-54 years)
:: - North Koreans (55-64 years)
:: - North Koreans (65 years and over)

:: - South Koreans (0-14 years)
:: - South Koreans (15-24 years)
:: - South Koreans (25-54 years)
:: - South Koreans (55-64 years)
:: - South Koreans (65 years and over)

:: - South Korea listed companies
:: - Foregin investors

:: '''Parameters'''
:: - North Korea GDP
:: - North Korea GDP growth

:: - South Korea GDP
:: - South Korea GDP growth

:: - North Korea area [sq. meters]
:: - South Korea area [sq. meters]

:: - North Korea unemployment rate
:: - South Korea unemployment rate
:: - South Korea average salary [[https://tradingeconomics.com/south-korea/wages]]

:: - North Korea suicide rate ([[https://www.theguardian.com/world/2014/sep/04/north-korea-suicide-rate-among-worst-world-who-report]])
:: - Income / Suicide Rate ratio ([[https://www.businessinsider.com/link-between-wealth-and-suicide-rates-san-francisco-federal-reserve-2012-11]])

:: - Migration rates from East to West Germany after the fall of the Iron Curtain [[https://www.demographic-research.org/volumes/vol11/7/11-7.pdf]] (will be used as a reference for random migration rates)

:: '''Targets of the simulation:'''

:: - Determine population distribution based on migration rates (random based on data from Eastern/Western Germany case) and population
:: - Determine unemployment in the reunited country
:: - Determine suicide rates of North Koreans based on welfare / amount of underage persons (students) / average salary / amount of retired persons
:: - Determine new GDP based on above data (foreign investors being random)

:: '''Data sources:'''

:: Apart from the sources linked above, the data on North Korea will be used from CIA website [[https://www.cia.gov/library/publications/the-world-factbook/geos/kn.html]], comparable data on South Korea will be used from the same source for consistence [[https://www.cia.gov/librarY/publications/the-world-factbook/geos/ks.html]] and other specific data on South Korea will be pulled from Wikipedia.

:: ''The running simulation should show charts of the suicide rates, unemployment and GDP in time and the absolute numbers for the population distribution.''

:: Please let me know if this narrowing-down and breakdown is sufficient :) Thank you.

:: [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 00:48, 20 December 2018 (CET)

::: The relevance of comparison with Germany is questionable, but, ok. Let's say there perhaps isn't any better comparison. Nevertheless, I still don't understand, how the simulation should work. How the agents will act? How it will be measured? How you will be able to calculate all the figures? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:28, 21 December 2018 (CET)

:::: OK, I thought about how I would realize the simulation in NetLogo and I see you were right about it being too complicated. So I tried to simplify my model even more to be doable:
:::: - The patches will be divided proportionally by area of the two countries, they will also be characterized by a certain portion of the initial GDP as their wealth.
:::: - The turtles representing Koreans will have initial wealth (also based on the initial GDP) and they will be migrating towards one of the two states based on their inclination to migrate to the other country. This inclination will be calculated randomly based on the East-West Germany migration data and their wealth.
:::: - On each tick, the simulation will determine:
::::: - if the turtle (Korean) has a job (landed one, got fired, is working, or didn't get hired) based semi-randomly on the wealth of the patch the turtle is on.
::::: - The wealth of the patch and turtle -> if the turtle is employed, it gains wealth and also generates a little wealth for the patch; If unemployed, it drains the wealth of the patch a little and its wealth decreases a little.
::::: - Based on the suicide rates, employment and wealth, it will also semi-randomly decide if the person is likely to kill themselves.
:::: That way we can at least simulate and see the wealth distribution, suicide rates and population distribution in a very simplified model... Does that makes sense or am I still in over my head? :) [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 19:20, 21 December 2018 (CET)

::::: To be honest, I am a bit skeptical about the results. As the assignment is based on vague assumptions, I think the results will be very general. On the other hand, I appreciate the level of preparation, which is above average. Hence, it is exceptionally '''approved''' and I hope you invest the same level of effort into the simulation itself. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:52, 31 December 2018 (CET)
:::::: Thank you! [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 12:58, 31 December 2018 (CET)

== Simulation proposal (bobj00) ([[User:Bobrekjiri|Bobrekjiri]] ([[User talk:Bobrekjiri|talk]]) 13:49, 19 December 2018 (CET)) ''(Not approved yet)'' ==

Topic/goal: '''Comparing the efficiency of Diamond interchange and Diverging diamond interchange'''

'''Definition of the problem:''' 
- [https://en.wikipedia.org/wiki/Diverging_diamond_interchange Diverging diamond interchange] is an alternative to Diamond interchange that is being used in France since 1970s and was brought to light recently (2009) in USA because it should be more effective than Diamond interchange in terms of waiting times and also in terms of safety (fewer crossing points of traffic). 
- Goal of the simulation is to measure if the statement about lower waiting times is correct and under which conditions (traffic load, traffic lights setup). 
- Throughput and waiting times will be measured under several traffic conditions, for example: most cars exiting highway are heading south or most cars entering highway are heading west, etc. 
- Model does not include simulation of traffic accidents, so the safety cannot be measured and will not be part of the simulation. 

'''Simulation environment:''' Netlogo
'''Approved''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:29, 21 December 2018 (CET)

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== Simulation proposal [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 16:52, 19 December 2018 (CET) ==

Topic/goal: '''Maze runner vs fire'''

'''Definition of the problem:''' 
- There will be n apartment with rooms and obstacles (tables, bed, bath...), in a random room will be a people (user selects how many), who will try to find the way out, in some other random place will be fire spreading rapidly. Agents will not be able to move through walls and obstacles. The purpose of this simulation is to simulate an escape plan for an apartment.

'''Simulation environment''': Netlogo

: What is the purpose of the simulation? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:30, 21 December 2018 (CET)
:: to find out whether a person who is lost in a building will survive. Imagine yourself in a bulding you have never been before and a fire appears. Wouldn’t it be interesting to know If you would find your way out? [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 22:51, 21 December 2018 (CET)
::: It is just a modification of our Building escape example. Ok, it could be doable, but there must be a clear and substantial added value. Your assignment proposal must be much much more deeply elaborated. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:56, 31 December 2018 (CET)
:::: Ok, edited. [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 01:53, 3 January 2019 (CET)
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==Simulation proposal [[User:qnesa01|qnesa01]] ==

Topic/goal: '''Traffic simulation Argentinska street'''

'''Situation:''' 
- Argentinska street is one of the important roads in Prague that connects Bubenské nábřeží with bridge “Barikádníků”. It leads from city centre and other parts of city outside to the northern part of the country, and to Germany or Poland. Moreover, Argentinska street connects hospital “Na Bulovce” with city centre and other parts. For emergency vehicles it is the way how to get faster, where help is needed.

'''Definition of the problem:''' 
- There is traffic on the road during mornings and evenings, which makes people wait sometimes hours to get out and more important it makes difficult pass for emergency vehicles.

'''Purpose of simulation:''' 
In the scope is part of Argentinska street from Bubenské nábřeží till Dělnická street plus street Za Viaduktem, part of Jateční and part of Tusarova street as they have influence on the whole situation of Argentinska traffic. The purpose of the simulation is to find ways how to make traffic less. In order to do it will be checked, first, if it is possible to change lights more efficiently for cars flow. Second, answer the question – if we can add only one line only to one direction, which direction we have to choose: to city centre or from city centre?

'''Simulation environment''': Simprocess; SUMO (for traffic representation)

'''Brief process of simulation :''' 
1) Data collection. Data will be collected manually (observation) and from HERE traffic API. Manually for morning, midday and evening during 30 mins each part of the day within one week. At the end of data collecting the average distribution will be made based on the data.
2) Real situation simulation
3) Based on simulation of real situation will be checked the efficiency of lights changes
4) The hypothetical model of adding one more line will be created based on simulation of real situation
5) Summary

: Ok, SUMO could be used for this. I just don't understand what you will simulate in SUMO, and what you will simulate in Simprocess, and why? The combination of two tools is uneasy, so there should be a good reason. However sounds interesting. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:41, 21 December 2018 (CET)
: The Simprocess will be used for problem solution and SUMO for traffic representation of ready solution. Because SUMO does not have strong performance in searching solution, but very good for clear representation of ready result. Combination of two tools will be useful for this case. [[User:qnesa01|qnesa01]] ([[User talk:qnesa01|talk]]) 21:47, 27 December 2018 (CET)
:: Sorry, I still don't understand. Please, could you describe, how the simulation will look like in Simprocess and in SUMO? What will be the data you pass from SUMO to Simprocess (or vice versa)? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:36, 31 December 2018 (CET)

::: As I have mentioned above, firstly I am going to simulate initial state (as it is now). This will be done in Simprocess and SUMO. In Simprocess will be used variables: time of lights change, distribution of cars number arriving, staying and leaving. Based on same variables, simulation in SUMO will be created to get map based view. Secondly, I would like to work with variables to answer the proposed questions. All changes will be done first in Simprocess to get optimal solution. And then based again on the result values of variables from Simprocess the map view in SUMO will be made. So, SUMO will be used for representation purpose, to show Simprocess solution on the map. [[User:qnesa01|qnesa01]] ([[User talk:qnesa01|talk]]) 11:27, 3 January 2019 (CET)
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== Simulation proposal [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) (Reworked, Not Approved) ==

Topic/goal: '''Slime mold simulation (Reworked, Not Approved)''' 

'''Explanation:''' 
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas,
such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular,
light can repel the slime mold and be a factor in triggering spore growth.

The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was
demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path.
Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus
collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest
routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

'''Definition of the problem:''' 
The ability to find the most effective route from one source of food to another is the key ability I'll be
using for my simulation. The behavior and the end result can be easily checked against the realistic data
provided from the recorded studies. The agents will be the mold unit itself, which is directly depended on
the neighbor agents and the environment. Parameters can be changed to create different environment and then
can be compared what would be the minimum strength/endurance + speed to according numbers of food sources.

'''Key parameters:'''

-number of "food" in the area (generated randomly) 
-number of origin points of the slime mold (generated randomly) 
-speed of spreading in which the mold is finding the food 
-strength/endurance of the mold - the ability to survive without food (effectively it is the "searching range" of the mold) 

'''Simulation environment''': Netlogo 

: Reworked into more detailed version as requested. [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) 15:21, 7 January 2019 (CET)
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== Simulation proposal [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 22:33, 19 December 2018 (CET) ==

Topic/goal: '''Medieval Battle Simulation'''

'''Definition of the problem:''' 

Two kingdoms come to a dispute and after extensive diplomacy had failed, they take up arms and go to battle. 
Each kingdom can have different number of units, but they each choose from the same kind of units (unit types are better against some and weaker to other). 
Each side has their own staging area, but within that area the units can spawn at random locations to test different strategic formations. 
When they meet in battle, they fight to the last man who wins the dispute for his king.

'''Purpose of simulation:''' 
It simulates medieval combat on battlefield between two sides. 
The user can select which type of units and how many will each kingdom have. 
Repeated simulation can lead to conclusions on what strategy the kings should focus on and which units they should train for successful reign when facing a violent foe.

'''Simulation environment:''' NetLogo

: I would narrow this down to testing battle strategies. Forget kingdoms. You can perform a research on some historical strategies, their pros and cons, choose some, and try to simulate them, and compare. If it sounds meaningful, please, redefine the assignment. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:48, 21 December 2018 (CET)

:: The part about kingdoms was more of a story telling. The objects in NetLogo would just be the units (of different types). I envisioned them to spawn at random on their given side of the plane, but if it's necessary I could include spawning in historical formations. Would that be ok? [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 11:00, 22 December 2018 (CET)

::: The assignment is too brief to check. Please, define it in detail. Theoretically, the assignment should be the only source for you to solve it. It means that in this phase you should have thought out most of the details. Which formations you will simulate, how exactly should it look like, what will be the results, how you will evaluate it... [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:43, 31 December 2018 (CET)

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== Simulation proposal [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 09:30, 20 December 2018 (CET) ==

Topic/goal: '''Proof of a business plan - simulation of capacities of a Café'''

'''Definition of the problem:''' 

At the moment we have a venue in a small town under construction which we would like to turn into a café. 
The spatial dispositions are set and now there are many questions like: how to set up tables, find out how many people can be at one time in the café, if the café is profitable when the amount of people coming in is low/medium/high, etc. 

'''Purpose of simulation:''' 
As said, I would like to simulate a process of people coming in to find out the right amount of seats and tables when knowing there will be just one staff member at the time. 
I would also like to find out whether it is even possible to manage the whole place being just one person responsible for everything and/or whether it is cost efficient. 
 
The output data should help us find out whether the whole concept is viable and based on the findings we could adjust the business plan.

'''Simulation environment:''' I would like to use Simprocess for the simulation of the venue setting and probably complement it with some calculations in Excel.

: I like the idea, just hesitate about the tool. As far as I understand, a substantial part of the whole thing is about the spatial arrangement of the café. Then Simprocess is not the first choice. Why do you want to use it? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:56, 21 December 2018 (CET)

::I liked that Simprocess allowed me to work with resources. And I see the tables and chairs as a resource, as well as the working power. If the flow of people coming in is well set up, I thought, by adjusting the resources, it should be possible to find out the optional setting. Do you propose any other tool to do that? I will be greatful for other ideas to improve the solution as it is a real problem we would like to solve. [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 10:21, 27 December 2018 (CET)

::: If you need to deal with spatial factors, NetLogo is definitely a better choice. If you omit the spatial characteristics, the simulation become trivial, what would not be enough for this paper. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 02:06, 31 December 2018 (CET)

:::: Ok, I can do the simulation in NetLogo and mind the spatial characteristics. I just thought the original idea was complex enought as it would put together several rather simple simulations and tasks - like finding out the right amount of visitors based on data from people that run cafés in different places (recalculating the number of visitors based on the wealthiness of the region, based on the capacity of the venue, the number of citizens and so on).
::::I believe I can go with netLogo for simulating the venue as well, although it is not completely clear now for me, how do I find out the right ammount of seats for example?
::::I can imagine a random movement of agents coming in taking a first not-taken seat. It can also be like the agent has a capacity (it can be group of 4 or just a pair or a single person visitor) and it could take the table/seat only in case there is enough space for the whole group. There could also be a quality parameters - like grading system for the seats - how far is it from the bar, is it near the toilet and so on. So yes, that might show that some places will be more popular then others. Also the agents might have a limit under which they dont go, like if they dont find a seat with quality high enough they will leave. Now when I am writing this down I think it might work although I still have some questions. Is this something you had in mind as well or am I on completely different track? Thanks. [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 11:26, 31 December 2018 (CET)

::::: All right, now I understand it better. For the purpose you mentioned, Simprocess could be fine. The only problem is that the simulation itself is rather simple. Let's stick to it, nevertheless, I will require to make it really in detail including obtaining real data and simulating all relevant aspects. '''Approved.''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:58, 31 December 2018 (CET)

== Simulation proposal [[User:Manj01|Manj01]] ([[User talk:Manj01|talk]]) 15:21, 21 December 2018 (CET) ==

Topic/goal: '''Effective class configuration a plane between Prague and Dubai'''

'''Definition of the problem:''' 

There is a new airline operating between Prague and Dubai. The want to configure their planes as effectively as possible. They have one second hand Boeing 777 (396 seats in economy class only configuration)

'''Purpose of simulation:''' 
Company wants to operate daily air route between Prague and Dubai. The company can have up to four classes - economy, economy plus, business and first. Seat in higher class takes more space, but generates more money. Prices are available from companies currently operating on this route. Demand predictions can be made based on class configurations used by companies already operating on this and similar routes (6-hours mainly holiday) destinations.

'''Simulation environment:''' I would like to use MS Excel to do Monte Carlo simulation.

:: I just wonder, where is the randomnes, as you want to just derive the configuration from the already operating competition. If it should be a simulation, you would have to have real daily data (for reasonable long period, a year minimum) for the demand for the flights (there and back) and also for the individual classes. Only then you are able to derive probability distributions for the simulation that would make sense. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:31, 21 December 2018 (CET)

::: Ok, these are not available, so I will try a completely different idea:

Topic/goal: '''Archiving maximum efficiency in ticket management of a small company (real-life based data)'''

'''Definition of the problem:''' 

A small company has support personnel, testers and developers in one office. They together solve tickets created by customers. These tickets sometimes get stuck in ticketing system, because the numbers of people working there are not perfect. Campany uses Kayako and Jira to manage tickets - from these systems, there will be a lot of real-life data to base the simulation on.

'''Purpose of simulation:''' 
The simulation aims to provide the ideal amount of support people, testers/analysts and developers to solve tickets as quick as possible, while there are constraints, such as company budget and lowered effectivity of too many people working on the same ticket.

'''Simulation environment:''' I would like to use Simprocess to model and optimize the workflow.
: All right, '''approved''', but bear in mind that a detailed simulation based on real data is expected.

== Simulation proposal (xpipj04) ==

Topic/goal: You are what you eat

'''Definition of the problem:''' 
Most people nowadays want to hit the gym or eat healthy to get fit and at the same time take a long high quality sleep and work effectively. All the success in life and your energy comes from the food (nutrition values) you consume a day and the regime you have. The new year is knocking the door and you want to make sure that you will plan your food and regime effectively so your life is in balance.

'''Purpose of simulation:''' 
Based on the input you choose the simulation should be able to give you the expected levels of achieved energy, work efficiency and especially if you are about to get fit or you will drop down to be a couch potato.

'''Input parameters''' 
- Food consumed - listed types of food with calculated nutrition values (protein, fat, sugar, energy) 
- Time spent at gym (kardio, workout, culturist) 
- Time spent at work - type of work (manual, manager) 
- Time spent sleeping 

'''Output''' 
- Your BMI 
- Your fitness level 
- Your work focus 
- Your energy level 

'''Where I will get the data? ''' 
- My roommate is a nutrition specialist and member of huge fitness project so his advice will be the source of my dependencies between values as well as values for different types of nutrition. 
- Nutrition plans. 

'''How will I get the output?''' 
I would like to use NetLogo to be able to see both values (numbers) and also monthly progress on the display (maybe a characted running between job, eating and gym. Showing HP bar? :D).
If this kind of simulation is not suitable for NetLogo then Vensim? I have no idea how would I transfer the problem into equitations which are required.

:: You got it right - it is Vensim topic without any doubt. Without mathematical formulation you can not do any simulation, so you have to deal with mathematical model formulation anyway.So, if Vensim is ok with you, than we can approve it. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 08:20, 23 December 2018 (CET)
:::: Then I will go with Vensim and try to put together something meaningful! [[User:Jan.pippal|Jan Pippal]]
:::::: OK. Then '''approved'''. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 12:29, 24 December 2018 (CET)

Assignments WS 2018/2019

2019-01-07T14:23:02Z

Kadj02: /* Simulation proposal Kadj02 (talk) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) */

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Please, put here your assignments. Do not forget to sign them. You can use <nowiki>~~~~</nowiki> (four tildas) for an automatic signature. Use Show preview in order to check the result before your final sumbition.
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Please, strive to formulate your assignment carefully. We expect an adequate effort to formulate the assignment as it is your semestral paper. Do not forget that your main goal is a research paper. It means your simulation model must generate the results that are specific, measurable and verifiable. Think twice how you will develop your model, which entities you will use, draw a model diagram, consider what you will measure. No sooner than when you have a good idea about the model, submit your assignment. And of course, read [[How to deal with the simulation assignment|How to deal with the simulation assignment]].
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Topics on gambling, cards, etc. are not welcome.
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In order to avoid possible confusion, please, check if you have added '''approved''' in bold somewhere in our comment under your submission. If there is no '''approved''', it means the assignment was not approved yet.
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== Simulation proposal ([[Xvegm00|Xvegm00]]) Simulation of semi-intelligent algae (Not approved yet)==

This Netlogo simulation aims to copy the behaviour of a symbiotic organism called physarum polycephalum. Physarum is actually a single cell organism, but when two or more cells meet, their membranes merge together and they work together to efficiently gather nutrition and multiply.
This simulation should mimic the spread and path creation of the algae, as well as its ability to solve the shortest path problem.
Video about physarum: [https://www.youtube.com/embed/HyzT5b0tNtk]

The algae should work in two modes: food search and optimisation. The food search part involves the algae spreading in a radial pattern, until it finds a foodsource. When it succeeds, it should optimise its pathways to allow for fastest nutrient transport.
The goal is for the algae to be able to find the shortest path to food source (and optimize - destroy/recontruct exisiting pathways). It should be able to work around obstacles as well. A test of function could be for the algae to find a path through a wall with three holes and to choose the proper hole (with shortest path).

Initial plan
There is an initial node, where the algae begins and from which it spreads.
Food is randomly distributed across the area, defined be a patch of certain color.
Algae spreads as agents, leaving behind patches as temporary algae. Temporary algae have a time to live, a timeout. When foodsource is found, nutrients travel as agents back to to initial node. When nutrients visit an algae patch, they reset its timeout. Thus, only the algae which has nutrients travelling on it can survive. With a properly applied randonmness, for the travel of nutrients as well as the agents, this should optimise the pathways.

''Assignment''
Title: Simulation of semi-intelligent algae

Course: 4IT496 Simulace systémů (v angličtině) (WS 2018/2019)

Author: Bc. Martin Vegner

Model type: Multiagent

Modeling tool: NetLogo

[[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 13:23, 30 December 2018 (CET)

: Generally, it could be done, but it is necessary to elaborate this assignment into greater detail. How you will measure the results? How you can say if it was successful or not? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 02:21, 31 December 2018 (CET)
:: Asiggnment updated. Please revise. [[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 14:33, 31 December 2018 (CET)
::: Ok, now I understand it better, how the simulation works, and it is fine. The only questionmark is still the results. What is the problem you study? What is the question you solve? How do you verify, your simulation solved the problem? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:30, 31 December 2018 (CET)
:::: It solves the travelling salesmen problem, which is algoritmically NP complete problem. However, it is solved through agents, which incorporates emergent intelligence, through orderly behaviour of agents. It explains how a group of algae, without any neurons or thinking organs, solves difficult problems. It shows, that there is a simple and low requirement solution to the problem. It offers a different solution to calculating the path, instead a simulation can be used to plan roads between cities for example. It can be verified, as i suggested in the assignment, by making it find the shortest path arround obstacles. It even adapts to changes in the topology.[[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 23:26, 1 January 2019 (CET)

== Simulation proposal ([[xkorj58|xkorj58]]) Find the thief (Not approved yet)==

This simulation should be created as a space search. There shall be two types of agents - first ones, police officers looking for a thief. Second a thief (moveable or imoveable) which is about to be found. Room itself could have obstacles. Police officers will have a vision, can have memory, could be various number of them and level of shared information about searched fields.

''Description''

Environment will have certain number of walls through which agent (police officer) can't see. In this environment will be thief to find (moving or stable). It will be a closed environment (walled from all sides), for the agent information about the environment will be inaccessible, he will not know, where the walls are and how many of them there is. It will be deterministic - every step of one of agents will have just one effect - on agent itself. This leads to a static environment - agents will be the only moving things in it. As the environment is closed it will have certain number of possible actions. Thus it will be discrete and dimensional.

Agents will at first randomly run through the space. It will have a vision (few patches in front of him). It will also save information about what he saw, therefore he will know where should he go to explore unseen locations. From this comes his intelligence. In situation with more agents, they will share this information about space and create for themselves a map of the environment (already searched patches).

''Assignment''

Title: Find the thief

Course: 4IT496 Simulace systémů (v angličtině) (WS 2018/2019)

Author: Bc. Jiří Korčák

Model type: Multiagent

Modeling tool: NetLogo

[[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 16:03, 17 December 2018 (CET)

: Sorry, but I don't understand what is this simulation good for. What meaningful problem do you solve? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:44, 31 December 2018 (CET)
::The problem should be about how memory, number of police officers and shared informations influence searching for a thief. It could have applications for AI in computer games (thats where you meet agents like this ones) or even in real life - most important thing when looking for something is: ... (when there is 20 of us looking for something, memory and shared information is not that important, etc.). [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 10:36, 31 December 2018 (CET)
::: The assignment is too brief. For the real situation, you definitely need stated where do you find relevant data to be able setting the parameters of the simulation. If you want to develop an intelligent agent for using in e.g. computer games, I am fine with that, but you need to define the environment, you need to define, how the agent should exactly behave, how his intelligence works, etc.
::: Please, choose one of the approaches (I would recommend the second one), and describe the problem really in detail. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:35, 31 December 2018 (CET)
:::: I think, I'll pick the second one. Up in describtion I tried to define the environment and the agents intelligence. I'm not sure if it's complex enough. What do you recommend in this situation and simulation to upgrade? Escpecially about the agents (officers and thiefs). Thanks for your answer. [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 02:48, 2 January 2019 (CET)

== Simulation proposal (dolj04) ==

Topic/goal: '''Optimal size of HDD for virtual Digitization server'''

Definition of the problem: 
- each day an average of 47 batches of documents is being processed by the server with average size per batch of 32 MB (calculated from customers server) 
- the number of batches changes a lot and cant be easily predicted so it will have to be taken into consideration (from sample: lowest number of batches scanned in a day is 13, the highest is 134) 
- the average size is not changing that much 
- (batch contains original scanned documents, extracted data in XML files, log files, enhanced images and searchable PDF) 
- backup images from scanning will stay on the server for 6 months (those are ''additional'' ~50 % of the batch size) 
- successfully processed batches older than 14 days are deleted every day 
- for precaution lets say around 5% of batches wont be processed correctly 
- those will stay on the server and will be processed every month by admins 

Simulation environment: Vensim

:: on what data you will base the simulation? I do not see any causal loops in the issue you are trying to solve, using Vesim does not make much sense then- this topic suits the Monte Carlo if you have the data to derive the parameters from. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:38, 18 December 2018 (CET)

:::: I would like to take the data at work as I have access to production server which is used by one of our customers for digitization and I will use Monte Carlo as you suggested.

::::::OK.'''Approved'''. Make sure that the derivation of probability distributions out of the real data for generating the random values is also part of your paper.[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 08:38, 20 December 2018 (CET)

== Simulation proposal (svem02 [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 18:42, 18 December 2018 (CET)) ==

Topic: '''likelihood of infection with flu'''

Definition of the problem: 
- everyone has a certain probability of getting sick with a flu, this model calculates the probability based on the people you are in contact with (two types of people, infected, not infected). Other variables and levels are available (e.g. infestation, total population 

Simulation environment: Vensim

:: on what data you would set up the simulation? how would you simulate the individual people and their connection in Vensim? (in my opinon this topic fits multiagent simulation) [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:30, 18 December 2018 (CET)

:::: I would base the simulation on how much one person interacts with others, depending on this variable the person would have some probability of getting sick thus the number of ill people would increase thus the probability of him getting sick would be higher and higher. The variable infestation would represent how much the illness is easily transimited to other people. [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 14:04, 19 December 2018 (CET)
:::::: I do not see it as simulation - not much of randomness, no causal feedback loops and pretty obvious result (the longer the simulation would run, the more sick people or that one gets sick) with no practical use. Not to mention, there is no data to derive the equations needed. Either reformulate it for the Netlogo so that it has some useful results based on some real data, or try something else. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 14:27, 19 December 2018 (CET)
:::::::: Ok, I will try something else. New proposal at the bottom of the page [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 16:46, 19 December 2018 (CET)
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== Simulation proposal ([[User:xkaij00|xkaij00]] ([[User talk:xkaij00|talk]]) 21:20, 18 December 2018 (CET)) ==

Topic: '''Social and economical effects of reunification of North & South Korea''' 
'''Definition of the problem:''' 
Let's hope one day South and North Korea will be reunited. That would mean a big fluctuation of people between the two separated states: 
- North Koreans will migrate to South Korea area, look for flats, try to get jobs and receive welfare. 
- South Koreans will invest in North Korea area and create jobs and factories there. 
''I would like to simulate:'' 
- What will be the population ratio of the two areas per square meter. 
- How many North Koreans will move to South Korea area after the reunification and how many of them will be on welfare and how much that will cost the new reunited country. 
- How much will the suicide rate change in Korea after the reunification since it's a known fact that defected North Koreans have a high suicide rate due to the fact they have difficulties to adjust to the new lifestyle and process propaganda-free information. 
- What will be the housing situation after the reunification. 
- How will the GDP of the new country possibly develop. 
- Possibly how much money will be needed from international help. 
'''Simulation environment:''' NetLogo

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: I must say it is a really interesting topic, but I am afraid it is a bit too ambitious. Please, if you are interested in this topic, elaborate in detail, how you would solve it. What agents would you use, what parameters, how the simulation would look like, on what data it should be based (and where you get them). And perhaps focus on fewer goals. To be honest, I am still not sure if this is doable, because of the need for extensive research. But, try to think about it yourself. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 19:26, 19 December 2018 (CET)
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:: Thank you for the feedback - I tried to break down and simplify the simulation:

:: '''Agents:'''

:: - North Koreans (0-14 years)
:: - North Koreans (15-24 years)
:: - North Koreans (25-54 years)
:: - North Koreans (55-64 years)
:: - North Koreans (65 years and over)

:: - South Koreans (0-14 years)
:: - South Koreans (15-24 years)
:: - South Koreans (25-54 years)
:: - South Koreans (55-64 years)
:: - South Koreans (65 years and over)

:: - South Korea listed companies
:: - Foregin investors

:: '''Parameters'''
:: - North Korea GDP
:: - North Korea GDP growth

:: - South Korea GDP
:: - South Korea GDP growth

:: - North Korea area [sq. meters]
:: - South Korea area [sq. meters]

:: - North Korea unemployment rate
:: - South Korea unemployment rate
:: - South Korea average salary [[https://tradingeconomics.com/south-korea/wages]]

:: - North Korea suicide rate ([[https://www.theguardian.com/world/2014/sep/04/north-korea-suicide-rate-among-worst-world-who-report]])
:: - Income / Suicide Rate ratio ([[https://www.businessinsider.com/link-between-wealth-and-suicide-rates-san-francisco-federal-reserve-2012-11]])

:: - Migration rates from East to West Germany after the fall of the Iron Curtain [[https://www.demographic-research.org/volumes/vol11/7/11-7.pdf]] (will be used as a reference for random migration rates)

:: '''Targets of the simulation:'''

:: - Determine population distribution based on migration rates (random based on data from Eastern/Western Germany case) and population
:: - Determine unemployment in the reunited country
:: - Determine suicide rates of North Koreans based on welfare / amount of underage persons (students) / average salary / amount of retired persons
:: - Determine new GDP based on above data (foreign investors being random)

:: '''Data sources:'''

:: Apart from the sources linked above, the data on North Korea will be used from CIA website [[https://www.cia.gov/library/publications/the-world-factbook/geos/kn.html]], comparable data on South Korea will be used from the same source for consistence [[https://www.cia.gov/librarY/publications/the-world-factbook/geos/ks.html]] and other specific data on South Korea will be pulled from Wikipedia.

:: ''The running simulation should show charts of the suicide rates, unemployment and GDP in time and the absolute numbers for the population distribution.''

:: Please let me know if this narrowing-down and breakdown is sufficient :) Thank you.

:: [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 00:48, 20 December 2018 (CET)

::: The relevance of comparison with Germany is questionable, but, ok. Let's say there perhaps isn't any better comparison. Nevertheless, I still don't understand, how the simulation should work. How the agents will act? How it will be measured? How you will be able to calculate all the figures? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:28, 21 December 2018 (CET)

:::: OK, I thought about how I would realize the simulation in NetLogo and I see you were right about it being too complicated. So I tried to simplify my model even more to be doable:
:::: - The patches will be divided proportionally by area of the two countries, they will also be characterized by a certain portion of the initial GDP as their wealth.
:::: - The turtles representing Koreans will have initial wealth (also based on the initial GDP) and they will be migrating towards one of the two states based on their inclination to migrate to the other country. This inclination will be calculated randomly based on the East-West Germany migration data and their wealth.
:::: - On each tick, the simulation will determine:
::::: - if the turtle (Korean) has a job (landed one, got fired, is working, or didn't get hired) based semi-randomly on the wealth of the patch the turtle is on.
::::: - The wealth of the patch and turtle -> if the turtle is employed, it gains wealth and also generates a little wealth for the patch; If unemployed, it drains the wealth of the patch a little and its wealth decreases a little.
::::: - Based on the suicide rates, employment and wealth, it will also semi-randomly decide if the person is likely to kill themselves.
:::: That way we can at least simulate and see the wealth distribution, suicide rates and population distribution in a very simplified model... Does that makes sense or am I still in over my head? :) [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 19:20, 21 December 2018 (CET)

::::: To be honest, I am a bit skeptical about the results. As the assignment is based on vague assumptions, I think the results will be very general. On the other hand, I appreciate the level of preparation, which is above average. Hence, it is exceptionally '''approved''' and I hope you invest the same level of effort into the simulation itself. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:52, 31 December 2018 (CET)
:::::: Thank you! [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 12:58, 31 December 2018 (CET)

== Simulation proposal (bobj00) ([[User:Bobrekjiri|Bobrekjiri]] ([[User talk:Bobrekjiri|talk]]) 13:49, 19 December 2018 (CET)) ''(Not approved yet)'' ==

Topic/goal: '''Comparing the efficiency of Diamond interchange and Diverging diamond interchange'''

'''Definition of the problem:''' 
- [https://en.wikipedia.org/wiki/Diverging_diamond_interchange Diverging diamond interchange] is an alternative to Diamond interchange that is being used in France since 1970s and was brought to light recently (2009) in USA because it should be more effective than Diamond interchange in terms of waiting times and also in terms of safety (fewer crossing points of traffic). 
- Goal of the simulation is to measure if the statement about lower waiting times is correct and under which conditions (traffic load, traffic lights setup). 
- Throughput and waiting times will be measured under several traffic conditions, for example: most cars exiting highway are heading south or most cars entering highway are heading west, etc. 
- Model does not include simulation of traffic accidents, so the safety cannot be measured and will not be part of the simulation. 

'''Simulation environment:''' Netlogo
'''Approved''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:29, 21 December 2018 (CET)

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== Simulation proposal [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 16:52, 19 December 2018 (CET) ==

Topic/goal: '''Maze runner vs fire'''

'''Definition of the problem:''' 
- There will be n apartment with rooms and obstacles (tables, bed, bath...), in a random room will be a people (user selects how many), who will try to find the way out, in some other random place will be fire spreading rapidly. Agents will not be able to move through walls and obstacles. The purpose of this simulation is to simulate an escape plan for an apartment.

'''Simulation environment''': Netlogo

: What is the purpose of the simulation? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:30, 21 December 2018 (CET)
:: to find out whether a person who is lost in a building will survive. Imagine yourself in a bulding you have never been before and a fire appears. Wouldn’t it be interesting to know If you would find your way out? [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 22:51, 21 December 2018 (CET)
::: It is just a modification of our Building escape example. Ok, it could be doable, but there must be a clear and substantial added value. Your assignment proposal must be much much more deeply elaborated. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:56, 31 December 2018 (CET)
:::: Ok, edited. [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 01:53, 3 January 2019 (CET)
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==Simulation proposal [[User:qnesa01|qnesa01]] ==

Topic/goal: '''Traffic simulation Argentinska street'''

'''Situation:''' 
- Argentinska street is one of the important roads in Prague that connects Bubenské nábřeží with bridge “Barikádníků”. It leads from city centre and other parts of city outside to the northern part of the country, and to Germany or Poland. Moreover, Argentinska street connects hospital “Na Bulovce” with city centre and other parts. For emergency vehicles it is the way how to get faster, where help is needed.

'''Definition of the problem:''' 
- There is traffic on the road during mornings and evenings, which makes people wait sometimes hours to get out and more important it makes difficult pass for emergency vehicles.

'''Purpose of simulation:''' 
In the scope is part of Argentinska street from Bubenské nábřeží till Dělnická street plus street Za Viaduktem, part of Jateční and part of Tusarova street as they have influence on the whole situation of Argentinska traffic. The purpose of the simulation is to find ways how to make traffic less. In order to do it will be checked, first, if it is possible to change lights more efficiently for cars flow. Second, answer the question – if we can add only one line only to one direction, which direction we have to choose: to city centre or from city centre?

'''Simulation environment''': Simprocess; SUMO (for traffic representation)

'''Brief process of simulation :''' 
1) Data collection. Data will be collected manually (observation) and from HERE traffic API. Manually for morning, midday and evening during 30 mins each part of the day within one week. At the end of data collecting the average distribution will be made based on the data.
2) Real situation simulation
3) Based on simulation of real situation will be checked the efficiency of lights changes
4) The hypothetical model of adding one more line will be created based on simulation of real situation
5) Summary

: Ok, SUMO could be used for this. I just don't understand what you will simulate in SUMO, and what you will simulate in Simprocess, and why? The combination of two tools is uneasy, so there should be a good reason. However sounds interesting. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:41, 21 December 2018 (CET)
: The Simprocess will be used for problem solution and SUMO for traffic representation of ready solution. Because SUMO does not have strong performance in searching solution, but very good for clear representation of ready result. Combination of two tools will be useful for this case. [[User:qnesa01|qnesa01]] ([[User talk:qnesa01|talk]]) 21:47, 27 December 2018 (CET)
:: Sorry, I still don't understand. Please, could you describe, how the simulation will look like in Simprocess and in SUMO? What will be the data you pass from SUMO to Simprocess (or vice versa)? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:36, 31 December 2018 (CET)

::: As I have mentioned above, firstly I am going to simulate initial state (as it is now). This will be done in Simprocess and SUMO. In Simprocess will be used variables: time of lights change, distribution of cars number arriving, staying and leaving. Based on same variables, simulation in SUMO will be created to get map based view. Secondly, I would like to work with variables to answer the proposed questions. All changes will be done first in Simprocess to get optimal solution. And then based again on the result values of variables from Simprocess the map view in SUMO will be made. So, SUMO will be used for representation purpose, to show Simprocess solution on the map. [[User:qnesa01|qnesa01]] ([[User talk:qnesa01|talk]]) 11:27, 3 January 2019 (CET)
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== Simulation proposal [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) ==

Topic/goal: '''Slime mold simulation (Reworked, Not Approved)''' 

'''Explanation:''' 
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas,
such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular,
light can repel the slime mold and be a factor in triggering spore growth.

The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was
demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path.
Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus
collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest
routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

'''Definition of the problem:''' 
The ability to find the most effective route from one source of food to another is the key ability I'll be
using for my simulation. The behavior and the end result can be easily checked against the realistic data
provided from the recorded studies. The agents will be the mold unit itself, which is directly depended on
the neighbor agents and the environment. Parameters can be changed to create different environment and then
can be compared what would be the minimum strength/endurance + speed to according numbers of food sources.

'''Key parameters:'''

-number of "food" in the area (generated randomly) 
-number of origin points of the slime mold (generated randomly) 
-speed of spreading in which the mold is finding the food 
-strength/endurance of the mold - the ability to survive without food (effectively it is the "searching range" of the mold) 

'''Simulation environment''': Netlogo 

: Reworked into more detailed version as requested. [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) 15:21, 7 January 2019 (CET)
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== Simulation proposal [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 22:33, 19 December 2018 (CET) ==

Topic/goal: '''Medieval Battle Simulation'''

'''Definition of the problem:''' 

Two kingdoms come to a dispute and after extensive diplomacy had failed, they take up arms and go to battle. 
Each kingdom can have different number of units, but they each choose from the same kind of units (unit types are better against some and weaker to other). 
Each side has their own staging area, but within that area the units can spawn at random locations to test different strategic formations. 
When they meet in battle, they fight to the last man who wins the dispute for his king.

'''Purpose of simulation:''' 
It simulates medieval combat on battlefield between two sides. 
The user can select which type of units and how many will each kingdom have. 
Repeated simulation can lead to conclusions on what strategy the kings should focus on and which units they should train for successful reign when facing a violent foe.

'''Simulation environment:''' NetLogo

: I would narrow this down to testing battle strategies. Forget kingdoms. You can perform a research on some historical strategies, their pros and cons, choose some, and try to simulate them, and compare. If it sounds meaningful, please, redefine the assignment. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:48, 21 December 2018 (CET)

:: The part about kingdoms was more of a story telling. The objects in NetLogo would just be the units (of different types). I envisioned them to spawn at random on their given side of the plane, but if it's necessary I could include spawning in historical formations. Would that be ok? [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 11:00, 22 December 2018 (CET)

::: The assignment is too brief to check. Please, define it in detail. Theoretically, the assignment should be the only source for you to solve it. It means that in this phase you should have thought out most of the details. Which formations you will simulate, how exactly should it look like, what will be the results, how you will evaluate it... [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:43, 31 December 2018 (CET)

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== Simulation proposal [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 09:30, 20 December 2018 (CET) ==

Topic/goal: '''Proof of a business plan - simulation of capacities of a Café'''

'''Definition of the problem:''' 

At the moment we have a venue in a small town under construction which we would like to turn into a café. 
The spatial dispositions are set and now there are many questions like: how to set up tables, find out how many people can be at one time in the café, if the café is profitable when the amount of people coming in is low/medium/high, etc. 

'''Purpose of simulation:''' 
As said, I would like to simulate a process of people coming in to find out the right amount of seats and tables when knowing there will be just one staff member at the time. 
I would also like to find out whether it is even possible to manage the whole place being just one person responsible for everything and/or whether it is cost efficient. 
 
The output data should help us find out whether the whole concept is viable and based on the findings we could adjust the business plan.

'''Simulation environment:''' I would like to use Simprocess for the simulation of the venue setting and probably complement it with some calculations in Excel.

: I like the idea, just hesitate about the tool. As far as I understand, a substantial part of the whole thing is about the spatial arrangement of the café. Then Simprocess is not the first choice. Why do you want to use it? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:56, 21 December 2018 (CET)

::I liked that Simprocess allowed me to work with resources. And I see the tables and chairs as a resource, as well as the working power. If the flow of people coming in is well set up, I thought, by adjusting the resources, it should be possible to find out the optional setting. Do you propose any other tool to do that? I will be greatful for other ideas to improve the solution as it is a real problem we would like to solve. [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 10:21, 27 December 2018 (CET)

::: If you need to deal with spatial factors, NetLogo is definitely a better choice. If you omit the spatial characteristics, the simulation become trivial, what would not be enough for this paper. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 02:06, 31 December 2018 (CET)

:::: Ok, I can do the simulation in NetLogo and mind the spatial characteristics. I just thought the original idea was complex enought as it would put together several rather simple simulations and tasks - like finding out the right amount of visitors based on data from people that run cafés in different places (recalculating the number of visitors based on the wealthiness of the region, based on the capacity of the venue, the number of citizens and so on).
::::I believe I can go with netLogo for simulating the venue as well, although it is not completely clear now for me, how do I find out the right ammount of seats for example?
::::I can imagine a random movement of agents coming in taking a first not-taken seat. It can also be like the agent has a capacity (it can be group of 4 or just a pair or a single person visitor) and it could take the table/seat only in case there is enough space for the whole group. There could also be a quality parameters - like grading system for the seats - how far is it from the bar, is it near the toilet and so on. So yes, that might show that some places will be more popular then others. Also the agents might have a limit under which they dont go, like if they dont find a seat with quality high enough they will leave. Now when I am writing this down I think it might work although I still have some questions. Is this something you had in mind as well or am I on completely different track? Thanks. [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 11:26, 31 December 2018 (CET)

::::: All right, now I understand it better. For the purpose you mentioned, Simprocess could be fine. The only problem is that the simulation itself is rather simple. Let's stick to it, nevertheless, I will require to make it really in detail including obtaining real data and simulating all relevant aspects. '''Approved.''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:58, 31 December 2018 (CET)

== Simulation proposal [[User:Manj01|Manj01]] ([[User talk:Manj01|talk]]) 15:21, 21 December 2018 (CET) ==

Topic/goal: '''Effective class configuration a plane between Prague and Dubai'''

'''Definition of the problem:''' 

There is a new airline operating between Prague and Dubai. The want to configure their planes as effectively as possible. They have one second hand Boeing 777 (396 seats in economy class only configuration)

'''Purpose of simulation:''' 
Company wants to operate daily air route between Prague and Dubai. The company can have up to four classes - economy, economy plus, business and first. Seat in higher class takes more space, but generates more money. Prices are available from companies currently operating on this route. Demand predictions can be made based on class configurations used by companies already operating on this and similar routes (6-hours mainly holiday) destinations.

'''Simulation environment:''' I would like to use MS Excel to do Monte Carlo simulation.

:: I just wonder, where is the randomnes, as you want to just derive the configuration from the already operating competition. If it should be a simulation, you would have to have real daily data (for reasonable long period, a year minimum) for the demand for the flights (there and back) and also for the individual classes. Only then you are able to derive probability distributions for the simulation that would make sense. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:31, 21 December 2018 (CET)

::: Ok, these are not available, so I will try a completely different idea:

Topic/goal: '''Archiving maximum efficiency in ticket management of a small company (real-life based data)'''

'''Definition of the problem:''' 

A small company has support personnel, testers and developers in one office. They together solve tickets created by customers. These tickets sometimes get stuck in ticketing system, because the numbers of people working there are not perfect. Campany uses Kayako and Jira to manage tickets - from these systems, there will be a lot of real-life data to base the simulation on.

'''Purpose of simulation:''' 
The simulation aims to provide the ideal amount of support people, testers/analysts and developers to solve tickets as quick as possible, while there are constraints, such as company budget and lowered effectivity of too many people working on the same ticket.

'''Simulation environment:''' I would like to use Simprocess to model and optimize the workflow.
: All right, '''approved''', but bear in mind that a detailed simulation based on real data is expected.

== Simulation proposal (xpipj04) ==

Topic/goal: You are what you eat

'''Definition of the problem:''' 
Most people nowadays want to hit the gym or eat healthy to get fit and at the same time take a long high quality sleep and work effectively. All the success in life and your energy comes from the food (nutrition values) you consume a day and the regime you have. The new year is knocking the door and you want to make sure that you will plan your food and regime effectively so your life is in balance.

'''Purpose of simulation:''' 
Based on the input you choose the simulation should be able to give you the expected levels of achieved energy, work efficiency and especially if you are about to get fit or you will drop down to be a couch potato.

'''Input parameters''' 
- Food consumed - listed types of food with calculated nutrition values (protein, fat, sugar, energy) 
- Time spent at gym (kardio, workout, culturist) 
- Time spent at work - type of work (manual, manager) 
- Time spent sleeping 

'''Output''' 
- Your BMI 
- Your fitness level 
- Your work focus 
- Your energy level 

'''Where I will get the data? ''' 
- My roommate is a nutrition specialist and member of huge fitness project so his advice will be the source of my dependencies between values as well as values for different types of nutrition. 
- Nutrition plans. 

'''How will I get the output?''' 
I would like to use NetLogo to be able to see both values (numbers) and also monthly progress on the display (maybe a characted running between job, eating and gym. Showing HP bar? :D).
If this kind of simulation is not suitable for NetLogo then Vensim? I have no idea how would I transfer the problem into equitations which are required.

:: You got it right - it is Vensim topic without any doubt. Without mathematical formulation you can not do any simulation, so you have to deal with mathematical model formulation anyway.So, if Vensim is ok with you, than we can approve it. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 08:20, 23 December 2018 (CET)
:::: Then I will go with Vensim and try to put together something meaningful! [[User:Jan.pippal|Jan Pippal]]
:::::: OK. Then '''approved'''. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 12:29, 24 December 2018 (CET)

Assignments WS 2018/2019

2019-01-07T14:22:36Z

Kadj02: /* Simulation proposal Kadj02 (talk) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) */

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Please, put here your assignments. Do not forget to sign them. You can use <nowiki>~~~~</nowiki> (four tildas) for an automatic signature. Use Show preview in order to check the result before your final sumbition.
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Please, strive to formulate your assignment carefully. We expect an adequate effort to formulate the assignment as it is your semestral paper. Do not forget that your main goal is a research paper. It means your simulation model must generate the results that are specific, measurable and verifiable. Think twice how you will develop your model, which entities you will use, draw a model diagram, consider what you will measure. No sooner than when you have a good idea about the model, submit your assignment. And of course, read [[How to deal with the simulation assignment|How to deal with the simulation assignment]].
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Topics on gambling, cards, etc. are not welcome.
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In order to avoid possible confusion, please, check if you have added '''approved''' in bold somewhere in our comment under your submission. If there is no '''approved''', it means the assignment was not approved yet.
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== Simulation proposal ([[Xvegm00|Xvegm00]]) Simulation of semi-intelligent algae (Not approved yet)==

This Netlogo simulation aims to copy the behaviour of a symbiotic organism called physarum polycephalum. Physarum is actually a single cell organism, but when two or more cells meet, their membranes merge together and they work together to efficiently gather nutrition and multiply.
This simulation should mimic the spread and path creation of the algae, as well as its ability to solve the shortest path problem.
Video about physarum: [https://www.youtube.com/embed/HyzT5b0tNtk]

The algae should work in two modes: food search and optimisation. The food search part involves the algae spreading in a radial pattern, until it finds a foodsource. When it succeeds, it should optimise its pathways to allow for fastest nutrient transport.
The goal is for the algae to be able to find the shortest path to food source (and optimize - destroy/recontruct exisiting pathways). It should be able to work around obstacles as well. A test of function could be for the algae to find a path through a wall with three holes and to choose the proper hole (with shortest path).

Initial plan
There is an initial node, where the algae begins and from which it spreads.
Food is randomly distributed across the area, defined be a patch of certain color.
Algae spreads as agents, leaving behind patches as temporary algae. Temporary algae have a time to live, a timeout. When foodsource is found, nutrients travel as agents back to to initial node. When nutrients visit an algae patch, they reset its timeout. Thus, only the algae which has nutrients travelling on it can survive. With a properly applied randonmness, for the travel of nutrients as well as the agents, this should optimise the pathways.

''Assignment''
Title: Simulation of semi-intelligent algae

Course: 4IT496 Simulace systémů (v angličtině) (WS 2018/2019)

Author: Bc. Martin Vegner

Model type: Multiagent

Modeling tool: NetLogo

[[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 13:23, 30 December 2018 (CET)

: Generally, it could be done, but it is necessary to elaborate this assignment into greater detail. How you will measure the results? How you can say if it was successful or not? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 02:21, 31 December 2018 (CET)
:: Asiggnment updated. Please revise. [[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 14:33, 31 December 2018 (CET)
::: Ok, now I understand it better, how the simulation works, and it is fine. The only questionmark is still the results. What is the problem you study? What is the question you solve? How do you verify, your simulation solved the problem? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:30, 31 December 2018 (CET)
:::: It solves the travelling salesmen problem, which is algoritmically NP complete problem. However, it is solved through agents, which incorporates emergent intelligence, through orderly behaviour of agents. It explains how a group of algae, without any neurons or thinking organs, solves difficult problems. It shows, that there is a simple and low requirement solution to the problem. It offers a different solution to calculating the path, instead a simulation can be used to plan roads between cities for example. It can be verified, as i suggested in the assignment, by making it find the shortest path arround obstacles. It even adapts to changes in the topology.[[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 23:26, 1 January 2019 (CET)

== Simulation proposal ([[xkorj58|xkorj58]]) Find the thief (Not approved yet)==

This simulation should be created as a space search. There shall be two types of agents - first ones, police officers looking for a thief. Second a thief (moveable or imoveable) which is about to be found. Room itself could have obstacles. Police officers will have a vision, can have memory, could be various number of them and level of shared information about searched fields.

''Description''

Environment will have certain number of walls through which agent (police officer) can't see. In this environment will be thief to find (moving or stable). It will be a closed environment (walled from all sides), for the agent information about the environment will be inaccessible, he will not know, where the walls are and how many of them there is. It will be deterministic - every step of one of agents will have just one effect - on agent itself. This leads to a static environment - agents will be the only moving things in it. As the environment is closed it will have certain number of possible actions. Thus it will be discrete and dimensional.

Agents will at first randomly run through the space. It will have a vision (few patches in front of him). It will also save information about what he saw, therefore he will know where should he go to explore unseen locations. From this comes his intelligence. In situation with more agents, they will share this information about space and create for themselves a map of the environment (already searched patches).

''Assignment''

Title: Find the thief

Course: 4IT496 Simulace systémů (v angličtině) (WS 2018/2019)

Author: Bc. Jiří Korčák

Model type: Multiagent

Modeling tool: NetLogo

[[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 16:03, 17 December 2018 (CET)

: Sorry, but I don't understand what is this simulation good for. What meaningful problem do you solve? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:44, 31 December 2018 (CET)
::The problem should be about how memory, number of police officers and shared informations influence searching for a thief. It could have applications for AI in computer games (thats where you meet agents like this ones) or even in real life - most important thing when looking for something is: ... (when there is 20 of us looking for something, memory and shared information is not that important, etc.). [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 10:36, 31 December 2018 (CET)
::: The assignment is too brief. For the real situation, you definitely need stated where do you find relevant data to be able setting the parameters of the simulation. If you want to develop an intelligent agent for using in e.g. computer games, I am fine with that, but you need to define the environment, you need to define, how the agent should exactly behave, how his intelligence works, etc.
::: Please, choose one of the approaches (I would recommend the second one), and describe the problem really in detail. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:35, 31 December 2018 (CET)
:::: I think, I'll pick the second one. Up in describtion I tried to define the environment and the agents intelligence. I'm not sure if it's complex enough. What do you recommend in this situation and simulation to upgrade? Escpecially about the agents (officers and thiefs). Thanks for your answer. [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 02:48, 2 January 2019 (CET)

== Simulation proposal (dolj04) ==

Topic/goal: '''Optimal size of HDD for virtual Digitization server'''

Definition of the problem: 
- each day an average of 47 batches of documents is being processed by the server with average size per batch of 32 MB (calculated from customers server) 
- the number of batches changes a lot and cant be easily predicted so it will have to be taken into consideration (from sample: lowest number of batches scanned in a day is 13, the highest is 134) 
- the average size is not changing that much 
- (batch contains original scanned documents, extracted data in XML files, log files, enhanced images and searchable PDF) 
- backup images from scanning will stay on the server for 6 months (those are ''additional'' ~50 % of the batch size) 
- successfully processed batches older than 14 days are deleted every day 
- for precaution lets say around 5% of batches wont be processed correctly 
- those will stay on the server and will be processed every month by admins 

Simulation environment: Vensim

:: on what data you will base the simulation? I do not see any causal loops in the issue you are trying to solve, using Vesim does not make much sense then- this topic suits the Monte Carlo if you have the data to derive the parameters from. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:38, 18 December 2018 (CET)

:::: I would like to take the data at work as I have access to production server which is used by one of our customers for digitization and I will use Monte Carlo as you suggested.

::::::OK.'''Approved'''. Make sure that the derivation of probability distributions out of the real data for generating the random values is also part of your paper.[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 08:38, 20 December 2018 (CET)

== Simulation proposal (svem02 [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 18:42, 18 December 2018 (CET)) ==

Topic: '''likelihood of infection with flu'''

Definition of the problem: 
- everyone has a certain probability of getting sick with a flu, this model calculates the probability based on the people you are in contact with (two types of people, infected, not infected). Other variables and levels are available (e.g. infestation, total population 

Simulation environment: Vensim

:: on what data you would set up the simulation? how would you simulate the individual people and their connection in Vensim? (in my opinon this topic fits multiagent simulation) [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:30, 18 December 2018 (CET)

:::: I would base the simulation on how much one person interacts with others, depending on this variable the person would have some probability of getting sick thus the number of ill people would increase thus the probability of him getting sick would be higher and higher. The variable infestation would represent how much the illness is easily transimited to other people. [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 14:04, 19 December 2018 (CET)
:::::: I do not see it as simulation - not much of randomness, no causal feedback loops and pretty obvious result (the longer the simulation would run, the more sick people or that one gets sick) with no practical use. Not to mention, there is no data to derive the equations needed. Either reformulate it for the Netlogo so that it has some useful results based on some real data, or try something else. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 14:27, 19 December 2018 (CET)
:::::::: Ok, I will try something else. New proposal at the bottom of the page [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 16:46, 19 December 2018 (CET)
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== Simulation proposal ([[User:xkaij00|xkaij00]] ([[User talk:xkaij00|talk]]) 21:20, 18 December 2018 (CET)) ==

Topic: '''Social and economical effects of reunification of North & South Korea''' 
'''Definition of the problem:''' 
Let's hope one day South and North Korea will be reunited. That would mean a big fluctuation of people between the two separated states: 
- North Koreans will migrate to South Korea area, look for flats, try to get jobs and receive welfare. 
- South Koreans will invest in North Korea area and create jobs and factories there. 
''I would like to simulate:'' 
- What will be the population ratio of the two areas per square meter. 
- How many North Koreans will move to South Korea area after the reunification and how many of them will be on welfare and how much that will cost the new reunited country. 
- How much will the suicide rate change in Korea after the reunification since it's a known fact that defected North Koreans have a high suicide rate due to the fact they have difficulties to adjust to the new lifestyle and process propaganda-free information. 
- What will be the housing situation after the reunification. 
- How will the GDP of the new country possibly develop. 
- Possibly how much money will be needed from international help. 
'''Simulation environment:''' NetLogo

----
: I must say it is a really interesting topic, but I am afraid it is a bit too ambitious. Please, if you are interested in this topic, elaborate in detail, how you would solve it. What agents would you use, what parameters, how the simulation would look like, on what data it should be based (and where you get them). And perhaps focus on fewer goals. To be honest, I am still not sure if this is doable, because of the need for extensive research. But, try to think about it yourself. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 19:26, 19 December 2018 (CET)
----
:: Thank you for the feedback - I tried to break down and simplify the simulation:

:: '''Agents:'''

:: - North Koreans (0-14 years)
:: - North Koreans (15-24 years)
:: - North Koreans (25-54 years)
:: - North Koreans (55-64 years)
:: - North Koreans (65 years and over)

:: - South Koreans (0-14 years)
:: - South Koreans (15-24 years)
:: - South Koreans (25-54 years)
:: - South Koreans (55-64 years)
:: - South Koreans (65 years and over)

:: - South Korea listed companies
:: - Foregin investors

:: '''Parameters'''
:: - North Korea GDP
:: - North Korea GDP growth

:: - South Korea GDP
:: - South Korea GDP growth

:: - North Korea area [sq. meters]
:: - South Korea area [sq. meters]

:: - North Korea unemployment rate
:: - South Korea unemployment rate
:: - South Korea average salary [[https://tradingeconomics.com/south-korea/wages]]

:: - North Korea suicide rate ([[https://www.theguardian.com/world/2014/sep/04/north-korea-suicide-rate-among-worst-world-who-report]])
:: - Income / Suicide Rate ratio ([[https://www.businessinsider.com/link-between-wealth-and-suicide-rates-san-francisco-federal-reserve-2012-11]])

:: - Migration rates from East to West Germany after the fall of the Iron Curtain [[https://www.demographic-research.org/volumes/vol11/7/11-7.pdf]] (will be used as a reference for random migration rates)

:: '''Targets of the simulation:'''

:: - Determine population distribution based on migration rates (random based on data from Eastern/Western Germany case) and population
:: - Determine unemployment in the reunited country
:: - Determine suicide rates of North Koreans based on welfare / amount of underage persons (students) / average salary / amount of retired persons
:: - Determine new GDP based on above data (foreign investors being random)

:: '''Data sources:'''

:: Apart from the sources linked above, the data on North Korea will be used from CIA website [[https://www.cia.gov/library/publications/the-world-factbook/geos/kn.html]], comparable data on South Korea will be used from the same source for consistence [[https://www.cia.gov/librarY/publications/the-world-factbook/geos/ks.html]] and other specific data on South Korea will be pulled from Wikipedia.

:: ''The running simulation should show charts of the suicide rates, unemployment and GDP in time and the absolute numbers for the population distribution.''

:: Please let me know if this narrowing-down and breakdown is sufficient :) Thank you.

:: [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 00:48, 20 December 2018 (CET)

::: The relevance of comparison with Germany is questionable, but, ok. Let's say there perhaps isn't any better comparison. Nevertheless, I still don't understand, how the simulation should work. How the agents will act? How it will be measured? How you will be able to calculate all the figures? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:28, 21 December 2018 (CET)

:::: OK, I thought about how I would realize the simulation in NetLogo and I see you were right about it being too complicated. So I tried to simplify my model even more to be doable:
:::: - The patches will be divided proportionally by area of the two countries, they will also be characterized by a certain portion of the initial GDP as their wealth.
:::: - The turtles representing Koreans will have initial wealth (also based on the initial GDP) and they will be migrating towards one of the two states based on their inclination to migrate to the other country. This inclination will be calculated randomly based on the East-West Germany migration data and their wealth.
:::: - On each tick, the simulation will determine:
::::: - if the turtle (Korean) has a job (landed one, got fired, is working, or didn't get hired) based semi-randomly on the wealth of the patch the turtle is on.
::::: - The wealth of the patch and turtle -> if the turtle is employed, it gains wealth and also generates a little wealth for the patch; If unemployed, it drains the wealth of the patch a little and its wealth decreases a little.
::::: - Based on the suicide rates, employment and wealth, it will also semi-randomly decide if the person is likely to kill themselves.
:::: That way we can at least simulate and see the wealth distribution, suicide rates and population distribution in a very simplified model... Does that makes sense or am I still in over my head? :) [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 19:20, 21 December 2018 (CET)

::::: To be honest, I am a bit skeptical about the results. As the assignment is based on vague assumptions, I think the results will be very general. On the other hand, I appreciate the level of preparation, which is above average. Hence, it is exceptionally '''approved''' and I hope you invest the same level of effort into the simulation itself. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:52, 31 December 2018 (CET)
:::::: Thank you! [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 12:58, 31 December 2018 (CET)

== Simulation proposal (bobj00) ([[User:Bobrekjiri|Bobrekjiri]] ([[User talk:Bobrekjiri|talk]]) 13:49, 19 December 2018 (CET)) ''(Not approved yet)'' ==

Topic/goal: '''Comparing the efficiency of Diamond interchange and Diverging diamond interchange'''

'''Definition of the problem:''' 
- [https://en.wikipedia.org/wiki/Diverging_diamond_interchange Diverging diamond interchange] is an alternative to Diamond interchange that is being used in France since 1970s and was brought to light recently (2009) in USA because it should be more effective than Diamond interchange in terms of waiting times and also in terms of safety (fewer crossing points of traffic). 
- Goal of the simulation is to measure if the statement about lower waiting times is correct and under which conditions (traffic load, traffic lights setup). 
- Throughput and waiting times will be measured under several traffic conditions, for example: most cars exiting highway are heading south or most cars entering highway are heading west, etc. 
- Model does not include simulation of traffic accidents, so the safety cannot be measured and will not be part of the simulation. 

'''Simulation environment:''' Netlogo
'''Approved''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:29, 21 December 2018 (CET)

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== Simulation proposal [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 16:52, 19 December 2018 (CET) ==

Topic/goal: '''Maze runner vs fire'''

'''Definition of the problem:''' 
- There will be n apartment with rooms and obstacles (tables, bed, bath...), in a random room will be a people (user selects how many), who will try to find the way out, in some other random place will be fire spreading rapidly. Agents will not be able to move through walls and obstacles. The purpose of this simulation is to simulate an escape plan for an apartment.

'''Simulation environment''': Netlogo

: What is the purpose of the simulation? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:30, 21 December 2018 (CET)
:: to find out whether a person who is lost in a building will survive. Imagine yourself in a bulding you have never been before and a fire appears. Wouldn’t it be interesting to know If you would find your way out? [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 22:51, 21 December 2018 (CET)
::: It is just a modification of our Building escape example. Ok, it could be doable, but there must be a clear and substantial added value. Your assignment proposal must be much much more deeply elaborated. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:56, 31 December 2018 (CET)
:::: Ok, edited. [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 01:53, 3 January 2019 (CET)
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==Simulation proposal [[User:qnesa01|qnesa01]] ==

Topic/goal: '''Traffic simulation Argentinska street'''

'''Situation:''' 
- Argentinska street is one of the important roads in Prague that connects Bubenské nábřeží with bridge “Barikádníků”. It leads from city centre and other parts of city outside to the northern part of the country, and to Germany or Poland. Moreover, Argentinska street connects hospital “Na Bulovce” with city centre and other parts. For emergency vehicles it is the way how to get faster, where help is needed.

'''Definition of the problem:''' 
- There is traffic on the road during mornings and evenings, which makes people wait sometimes hours to get out and more important it makes difficult pass for emergency vehicles.

'''Purpose of simulation:''' 
In the scope is part of Argentinska street from Bubenské nábřeží till Dělnická street plus street Za Viaduktem, part of Jateční and part of Tusarova street as they have influence on the whole situation of Argentinska traffic. The purpose of the simulation is to find ways how to make traffic less. In order to do it will be checked, first, if it is possible to change lights more efficiently for cars flow. Second, answer the question – if we can add only one line only to one direction, which direction we have to choose: to city centre or from city centre?

'''Simulation environment''': Simprocess; SUMO (for traffic representation)

'''Brief process of simulation :''' 
1) Data collection. Data will be collected manually (observation) and from HERE traffic API. Manually for morning, midday and evening during 30 mins each part of the day within one week. At the end of data collecting the average distribution will be made based on the data.
2) Real situation simulation
3) Based on simulation of real situation will be checked the efficiency of lights changes
4) The hypothetical model of adding one more line will be created based on simulation of real situation
5) Summary

: Ok, SUMO could be used for this. I just don't understand what you will simulate in SUMO, and what you will simulate in Simprocess, and why? The combination of two tools is uneasy, so there should be a good reason. However sounds interesting. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:41, 21 December 2018 (CET)
: The Simprocess will be used for problem solution and SUMO for traffic representation of ready solution. Because SUMO does not have strong performance in searching solution, but very good for clear representation of ready result. Combination of two tools will be useful for this case. [[User:qnesa01|qnesa01]] ([[User talk:qnesa01|talk]]) 21:47, 27 December 2018 (CET)
:: Sorry, I still don't understand. Please, could you describe, how the simulation will look like in Simprocess and in SUMO? What will be the data you pass from SUMO to Simprocess (or vice versa)? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:36, 31 December 2018 (CET)

::: As I have mentioned above, firstly I am going to simulate initial state (as it is now). This will be done in Simprocess and SUMO. In Simprocess will be used variables: time of lights change, distribution of cars number arriving, staying and leaving. Based on same variables, simulation in SUMO will be created to get map based view. Secondly, I would like to work with variables to answer the proposed questions. All changes will be done first in Simprocess to get optimal solution. And then based again on the result values of variables from Simprocess the map view in SUMO will be made. So, SUMO will be used for representation purpose, to show Simprocess solution on the map. [[User:qnesa01|qnesa01]] ([[User talk:qnesa01|talk]]) 11:27, 3 January 2019 (CET)
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== Simulation proposal [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) ==

Topic/goal: '''Slime mold simulation (Reworked, Not Approved)''' 

'''Explanation:''' 
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas,
such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular,
light can repel the slime mold and be a factor in triggering spore growth.

The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was
demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path.
Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus
collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest
routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

'''Definition of the problem:''' 
The ability to find the most effective route from one source of food to another is the key ability I'll be
using for my simulation. The behavior and the end result can be easily checked against the realistic data
provided from the recorded studies. The agents will be the mold unit itself, which is directly depended on
the neighbor agents and the environment. Parameters can be changed to create different environment and then
can be compared what would be the minimum strength/endurance + speed to according numbers of food sources.

'''Key parameters:'''

-number of "food" in the area (generated randomly)
-number of origin points of the slime mold (generated randomly)
-speed of spreading in which the mold is finding the food
-strength/endurance of the mold - the ability to survive without food (effectively it is the "searching range" of the mold)

'''Simulation environment''': Netlogo

: Reworked into more detailed version as requested. [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) 15:21, 7 January 2019 (CET)
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== Simulation proposal [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 22:33, 19 December 2018 (CET) ==

Topic/goal: '''Medieval Battle Simulation'''

'''Definition of the problem:''' 

Two kingdoms come to a dispute and after extensive diplomacy had failed, they take up arms and go to battle. 
Each kingdom can have different number of units, but they each choose from the same kind of units (unit types are better against some and weaker to other). 
Each side has their own staging area, but within that area the units can spawn at random locations to test different strategic formations. 
When they meet in battle, they fight to the last man who wins the dispute for his king.

'''Purpose of simulation:''' 
It simulates medieval combat on battlefield between two sides. 
The user can select which type of units and how many will each kingdom have. 
Repeated simulation can lead to conclusions on what strategy the kings should focus on and which units they should train for successful reign when facing a violent foe.

'''Simulation environment:''' NetLogo

: I would narrow this down to testing battle strategies. Forget kingdoms. You can perform a research on some historical strategies, their pros and cons, choose some, and try to simulate them, and compare. If it sounds meaningful, please, redefine the assignment. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:48, 21 December 2018 (CET)

:: The part about kingdoms was more of a story telling. The objects in NetLogo would just be the units (of different types). I envisioned them to spawn at random on their given side of the plane, but if it's necessary I could include spawning in historical formations. Would that be ok? [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 11:00, 22 December 2018 (CET)

::: The assignment is too brief to check. Please, define it in detail. Theoretically, the assignment should be the only source for you to solve it. It means that in this phase you should have thought out most of the details. Which formations you will simulate, how exactly should it look like, what will be the results, how you will evaluate it... [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:43, 31 December 2018 (CET)

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== Simulation proposal [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 09:30, 20 December 2018 (CET) ==

Topic/goal: '''Proof of a business plan - simulation of capacities of a Café'''

'''Definition of the problem:''' 

At the moment we have a venue in a small town under construction which we would like to turn into a café. 
The spatial dispositions are set and now there are many questions like: how to set up tables, find out how many people can be at one time in the café, if the café is profitable when the amount of people coming in is low/medium/high, etc. 

'''Purpose of simulation:''' 
As said, I would like to simulate a process of people coming in to find out the right amount of seats and tables when knowing there will be just one staff member at the time. 
I would also like to find out whether it is even possible to manage the whole place being just one person responsible for everything and/or whether it is cost efficient. 
 
The output data should help us find out whether the whole concept is viable and based on the findings we could adjust the business plan.

'''Simulation environment:''' I would like to use Simprocess for the simulation of the venue setting and probably complement it with some calculations in Excel.

: I like the idea, just hesitate about the tool. As far as I understand, a substantial part of the whole thing is about the spatial arrangement of the café. Then Simprocess is not the first choice. Why do you want to use it? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:56, 21 December 2018 (CET)

::I liked that Simprocess allowed me to work with resources. And I see the tables and chairs as a resource, as well as the working power. If the flow of people coming in is well set up, I thought, by adjusting the resources, it should be possible to find out the optional setting. Do you propose any other tool to do that? I will be greatful for other ideas to improve the solution as it is a real problem we would like to solve. [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 10:21, 27 December 2018 (CET)

::: If you need to deal with spatial factors, NetLogo is definitely a better choice. If you omit the spatial characteristics, the simulation become trivial, what would not be enough for this paper. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 02:06, 31 December 2018 (CET)

:::: Ok, I can do the simulation in NetLogo and mind the spatial characteristics. I just thought the original idea was complex enought as it would put together several rather simple simulations and tasks - like finding out the right amount of visitors based on data from people that run cafés in different places (recalculating the number of visitors based on the wealthiness of the region, based on the capacity of the venue, the number of citizens and so on).
::::I believe I can go with netLogo for simulating the venue as well, although it is not completely clear now for me, how do I find out the right ammount of seats for example?
::::I can imagine a random movement of agents coming in taking a first not-taken seat. It can also be like the agent has a capacity (it can be group of 4 or just a pair or a single person visitor) and it could take the table/seat only in case there is enough space for the whole group. There could also be a quality parameters - like grading system for the seats - how far is it from the bar, is it near the toilet and so on. So yes, that might show that some places will be more popular then others. Also the agents might have a limit under which they dont go, like if they dont find a seat with quality high enough they will leave. Now when I am writing this down I think it might work although I still have some questions. Is this something you had in mind as well or am I on completely different track? Thanks. [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 11:26, 31 December 2018 (CET)

::::: All right, now I understand it better. For the purpose you mentioned, Simprocess could be fine. The only problem is that the simulation itself is rather simple. Let's stick to it, nevertheless, I will require to make it really in detail including obtaining real data and simulating all relevant aspects. '''Approved.''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:58, 31 December 2018 (CET)

== Simulation proposal [[User:Manj01|Manj01]] ([[User talk:Manj01|talk]]) 15:21, 21 December 2018 (CET) ==

Topic/goal: '''Effective class configuration a plane between Prague and Dubai'''

'''Definition of the problem:''' 

There is a new airline operating between Prague and Dubai. The want to configure their planes as effectively as possible. They have one second hand Boeing 777 (396 seats in economy class only configuration)

'''Purpose of simulation:''' 
Company wants to operate daily air route between Prague and Dubai. The company can have up to four classes - economy, economy plus, business and first. Seat in higher class takes more space, but generates more money. Prices are available from companies currently operating on this route. Demand predictions can be made based on class configurations used by companies already operating on this and similar routes (6-hours mainly holiday) destinations.

'''Simulation environment:''' I would like to use MS Excel to do Monte Carlo simulation.

:: I just wonder, where is the randomnes, as you want to just derive the configuration from the already operating competition. If it should be a simulation, you would have to have real daily data (for reasonable long period, a year minimum) for the demand for the flights (there and back) and also for the individual classes. Only then you are able to derive probability distributions for the simulation that would make sense. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:31, 21 December 2018 (CET)

::: Ok, these are not available, so I will try a completely different idea:

Topic/goal: '''Archiving maximum efficiency in ticket management of a small company (real-life based data)'''

'''Definition of the problem:''' 

A small company has support personnel, testers and developers in one office. They together solve tickets created by customers. These tickets sometimes get stuck in ticketing system, because the numbers of people working there are not perfect. Campany uses Kayako and Jira to manage tickets - from these systems, there will be a lot of real-life data to base the simulation on.

'''Purpose of simulation:''' 
The simulation aims to provide the ideal amount of support people, testers/analysts and developers to solve tickets as quick as possible, while there are constraints, such as company budget and lowered effectivity of too many people working on the same ticket.

'''Simulation environment:''' I would like to use Simprocess to model and optimize the workflow.
: All right, '''approved''', but bear in mind that a detailed simulation based on real data is expected.

== Simulation proposal (xpipj04) ==

Topic/goal: You are what you eat

'''Definition of the problem:''' 
Most people nowadays want to hit the gym or eat healthy to get fit and at the same time take a long high quality sleep and work effectively. All the success in life and your energy comes from the food (nutrition values) you consume a day and the regime you have. The new year is knocking the door and you want to make sure that you will plan your food and regime effectively so your life is in balance.

'''Purpose of simulation:''' 
Based on the input you choose the simulation should be able to give you the expected levels of achieved energy, work efficiency and especially if you are about to get fit or you will drop down to be a couch potato.

'''Input parameters''' 
- Food consumed - listed types of food with calculated nutrition values (protein, fat, sugar, energy) 
- Time spent at gym (kardio, workout, culturist) 
- Time spent at work - type of work (manual, manager) 
- Time spent sleeping 

'''Output''' 
- Your BMI 
- Your fitness level 
- Your work focus 
- Your energy level 

'''Where I will get the data? ''' 
- My roommate is a nutrition specialist and member of huge fitness project so his advice will be the source of my dependencies between values as well as values for different types of nutrition. 
- Nutrition plans. 

'''How will I get the output?''' 
I would like to use NetLogo to be able to see both values (numbers) and also monthly progress on the display (maybe a characted running between job, eating and gym. Showing HP bar? :D).
If this kind of simulation is not suitable for NetLogo then Vensim? I have no idea how would I transfer the problem into equitations which are required.

:: You got it right - it is Vensim topic without any doubt. Without mathematical formulation you can not do any simulation, so you have to deal with mathematical model formulation anyway.So, if Vensim is ok with you, than we can approve it. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 08:20, 23 December 2018 (CET)
:::: Then I will go with Vensim and try to put together something meaningful! [[User:Jan.pippal|Jan Pippal]]
:::::: OK. Then '''approved'''. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 12:29, 24 December 2018 (CET)

Assignments WS 2018/2019

2019-01-07T14:21:42Z

Kadj02: /* Simulation proposal Kadj02 (talk) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) */

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Please, put here your assignments. Do not forget to sign them. You can use <nowiki>~~~~</nowiki> (four tildas) for an automatic signature. Use Show preview in order to check the result before your final sumbition.
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Please, strive to formulate your assignment carefully. We expect an adequate effort to formulate the assignment as it is your semestral paper. Do not forget that your main goal is a research paper. It means your simulation model must generate the results that are specific, measurable and verifiable. Think twice how you will develop your model, which entities you will use, draw a model diagram, consider what you will measure. No sooner than when you have a good idea about the model, submit your assignment. And of course, read [[How to deal with the simulation assignment|How to deal with the simulation assignment]].
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Topics on gambling, cards, etc. are not welcome.
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In order to avoid possible confusion, please, check if you have added '''approved''' in bold somewhere in our comment under your submission. If there is no '''approved''', it means the assignment was not approved yet.
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== Simulation proposal ([[Xvegm00|Xvegm00]]) Simulation of semi-intelligent algae (Not approved yet)==

This Netlogo simulation aims to copy the behaviour of a symbiotic organism called physarum polycephalum. Physarum is actually a single cell organism, but when two or more cells meet, their membranes merge together and they work together to efficiently gather nutrition and multiply.
This simulation should mimic the spread and path creation of the algae, as well as its ability to solve the shortest path problem.
Video about physarum: [https://www.youtube.com/embed/HyzT5b0tNtk]

The algae should work in two modes: food search and optimisation. The food search part involves the algae spreading in a radial pattern, until it finds a foodsource. When it succeeds, it should optimise its pathways to allow for fastest nutrient transport.
The goal is for the algae to be able to find the shortest path to food source (and optimize - destroy/recontruct exisiting pathways). It should be able to work around obstacles as well. A test of function could be for the algae to find a path through a wall with three holes and to choose the proper hole (with shortest path).

Initial plan
There is an initial node, where the algae begins and from which it spreads.
Food is randomly distributed across the area, defined be a patch of certain color.
Algae spreads as agents, leaving behind patches as temporary algae. Temporary algae have a time to live, a timeout. When foodsource is found, nutrients travel as agents back to to initial node. When nutrients visit an algae patch, they reset its timeout. Thus, only the algae which has nutrients travelling on it can survive. With a properly applied randonmness, for the travel of nutrients as well as the agents, this should optimise the pathways.

''Assignment''
Title: Simulation of semi-intelligent algae

Course: 4IT496 Simulace systémů (v angličtině) (WS 2018/2019)

Author: Bc. Martin Vegner

Model type: Multiagent

Modeling tool: NetLogo

[[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 13:23, 30 December 2018 (CET)

: Generally, it could be done, but it is necessary to elaborate this assignment into greater detail. How you will measure the results? How you can say if it was successful or not? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 02:21, 31 December 2018 (CET)
:: Asiggnment updated. Please revise. [[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 14:33, 31 December 2018 (CET)
::: Ok, now I understand it better, how the simulation works, and it is fine. The only questionmark is still the results. What is the problem you study? What is the question you solve? How do you verify, your simulation solved the problem? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:30, 31 December 2018 (CET)
:::: It solves the travelling salesmen problem, which is algoritmically NP complete problem. However, it is solved through agents, which incorporates emergent intelligence, through orderly behaviour of agents. It explains how a group of algae, without any neurons or thinking organs, solves difficult problems. It shows, that there is a simple and low requirement solution to the problem. It offers a different solution to calculating the path, instead a simulation can be used to plan roads between cities for example. It can be verified, as i suggested in the assignment, by making it find the shortest path arround obstacles. It even adapts to changes in the topology.[[User:Xvegm00|Xvegm00]] ([[User talk:Xvegm00|talk]]) 23:26, 1 January 2019 (CET)

== Simulation proposal ([[xkorj58|xkorj58]]) Find the thief (Not approved yet)==

This simulation should be created as a space search. There shall be two types of agents - first ones, police officers looking for a thief. Second a thief (moveable or imoveable) which is about to be found. Room itself could have obstacles. Police officers will have a vision, can have memory, could be various number of them and level of shared information about searched fields.

''Description''

Environment will have certain number of walls through which agent (police officer) can't see. In this environment will be thief to find (moving or stable). It will be a closed environment (walled from all sides), for the agent information about the environment will be inaccessible, he will not know, where the walls are and how many of them there is. It will be deterministic - every step of one of agents will have just one effect - on agent itself. This leads to a static environment - agents will be the only moving things in it. As the environment is closed it will have certain number of possible actions. Thus it will be discrete and dimensional.

Agents will at first randomly run through the space. It will have a vision (few patches in front of him). It will also save information about what he saw, therefore he will know where should he go to explore unseen locations. From this comes his intelligence. In situation with more agents, they will share this information about space and create for themselves a map of the environment (already searched patches).

''Assignment''

Title: Find the thief

Course: 4IT496 Simulace systémů (v angličtině) (WS 2018/2019)

Author: Bc. Jiří Korčák

Model type: Multiagent

Modeling tool: NetLogo

[[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 16:03, 17 December 2018 (CET)

: Sorry, but I don't understand what is this simulation good for. What meaningful problem do you solve? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:44, 31 December 2018 (CET)
::The problem should be about how memory, number of police officers and shared informations influence searching for a thief. It could have applications for AI in computer games (thats where you meet agents like this ones) or even in real life - most important thing when looking for something is: ... (when there is 20 of us looking for something, memory and shared information is not that important, etc.). [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 10:36, 31 December 2018 (CET)
::: The assignment is too brief. For the real situation, you definitely need stated where do you find relevant data to be able setting the parameters of the simulation. If you want to develop an intelligent agent for using in e.g. computer games, I am fine with that, but you need to define the environment, you need to define, how the agent should exactly behave, how his intelligence works, etc.
::: Please, choose one of the approaches (I would recommend the second one), and describe the problem really in detail. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:35, 31 December 2018 (CET)
:::: I think, I'll pick the second one. Up in describtion I tried to define the environment and the agents intelligence. I'm not sure if it's complex enough. What do you recommend in this situation and simulation to upgrade? Escpecially about the agents (officers and thiefs). Thanks for your answer. [[User:Xkorj58|Xkorj58]] ([[User talk:Xkorj58|talk]]) 02:48, 2 January 2019 (CET)

== Simulation proposal (dolj04) ==

Topic/goal: '''Optimal size of HDD for virtual Digitization server'''

Definition of the problem: 
- each day an average of 47 batches of documents is being processed by the server with average size per batch of 32 MB (calculated from customers server) 
- the number of batches changes a lot and cant be easily predicted so it will have to be taken into consideration (from sample: lowest number of batches scanned in a day is 13, the highest is 134) 
- the average size is not changing that much 
- (batch contains original scanned documents, extracted data in XML files, log files, enhanced images and searchable PDF) 
- backup images from scanning will stay on the server for 6 months (those are ''additional'' ~50 % of the batch size) 
- successfully processed batches older than 14 days are deleted every day 
- for precaution lets say around 5% of batches wont be processed correctly 
- those will stay on the server and will be processed every month by admins 

Simulation environment: Vensim

:: on what data you will base the simulation? I do not see any causal loops in the issue you are trying to solve, using Vesim does not make much sense then- this topic suits the Monte Carlo if you have the data to derive the parameters from. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:38, 18 December 2018 (CET)

:::: I would like to take the data at work as I have access to production server which is used by one of our customers for digitization and I will use Monte Carlo as you suggested.

::::::OK.'''Approved'''. Make sure that the derivation of probability distributions out of the real data for generating the random values is also part of your paper.[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 08:38, 20 December 2018 (CET)

== Simulation proposal (svem02 [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 18:42, 18 December 2018 (CET)) ==

Topic: '''likelihood of infection with flu'''

Definition of the problem: 
- everyone has a certain probability of getting sick with a flu, this model calculates the probability based on the people you are in contact with (two types of people, infected, not infected). Other variables and levels are available (e.g. infestation, total population 

Simulation environment: Vensim

:: on what data you would set up the simulation? how would you simulate the individual people and their connection in Vensim? (in my opinon this topic fits multiagent simulation) [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:30, 18 December 2018 (CET)

:::: I would base the simulation on how much one person interacts with others, depending on this variable the person would have some probability of getting sick thus the number of ill people would increase thus the probability of him getting sick would be higher and higher. The variable infestation would represent how much the illness is easily transimited to other people. [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 14:04, 19 December 2018 (CET)
:::::: I do not see it as simulation - not much of randomness, no causal feedback loops and pretty obvious result (the longer the simulation would run, the more sick people or that one gets sick) with no practical use. Not to mention, there is no data to derive the equations needed. Either reformulate it for the Netlogo so that it has some useful results based on some real data, or try something else. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 14:27, 19 December 2018 (CET)
:::::::: Ok, I will try something else. New proposal at the bottom of the page [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 16:46, 19 December 2018 (CET)
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== Simulation proposal ([[User:xkaij00|xkaij00]] ([[User talk:xkaij00|talk]]) 21:20, 18 December 2018 (CET)) ==

Topic: '''Social and economical effects of reunification of North & South Korea''' 
'''Definition of the problem:''' 
Let's hope one day South and North Korea will be reunited. That would mean a big fluctuation of people between the two separated states: 
- North Koreans will migrate to South Korea area, look for flats, try to get jobs and receive welfare. 
- South Koreans will invest in North Korea area and create jobs and factories there. 
''I would like to simulate:'' 
- What will be the population ratio of the two areas per square meter. 
- How many North Koreans will move to South Korea area after the reunification and how many of them will be on welfare and how much that will cost the new reunited country. 
- How much will the suicide rate change in Korea after the reunification since it's a known fact that defected North Koreans have a high suicide rate due to the fact they have difficulties to adjust to the new lifestyle and process propaganda-free information. 
- What will be the housing situation after the reunification. 
- How will the GDP of the new country possibly develop. 
- Possibly how much money will be needed from international help. 
'''Simulation environment:''' NetLogo

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: I must say it is a really interesting topic, but I am afraid it is a bit too ambitious. Please, if you are interested in this topic, elaborate in detail, how you would solve it. What agents would you use, what parameters, how the simulation would look like, on what data it should be based (and where you get them). And perhaps focus on fewer goals. To be honest, I am still not sure if this is doable, because of the need for extensive research. But, try to think about it yourself. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 19:26, 19 December 2018 (CET)
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:: Thank you for the feedback - I tried to break down and simplify the simulation:

:: '''Agents:'''

:: - North Koreans (0-14 years)
:: - North Koreans (15-24 years)
:: - North Koreans (25-54 years)
:: - North Koreans (55-64 years)
:: - North Koreans (65 years and over)

:: - South Koreans (0-14 years)
:: - South Koreans (15-24 years)
:: - South Koreans (25-54 years)
:: - South Koreans (55-64 years)
:: - South Koreans (65 years and over)

:: - South Korea listed companies
:: - Foregin investors

:: '''Parameters'''
:: - North Korea GDP
:: - North Korea GDP growth

:: - South Korea GDP
:: - South Korea GDP growth

:: - North Korea area [sq. meters]
:: - South Korea area [sq. meters]

:: - North Korea unemployment rate
:: - South Korea unemployment rate
:: - South Korea average salary [[https://tradingeconomics.com/south-korea/wages]]

:: - North Korea suicide rate ([[https://www.theguardian.com/world/2014/sep/04/north-korea-suicide-rate-among-worst-world-who-report]])
:: - Income / Suicide Rate ratio ([[https://www.businessinsider.com/link-between-wealth-and-suicide-rates-san-francisco-federal-reserve-2012-11]])

:: - Migration rates from East to West Germany after the fall of the Iron Curtain [[https://www.demographic-research.org/volumes/vol11/7/11-7.pdf]] (will be used as a reference for random migration rates)

:: '''Targets of the simulation:'''

:: - Determine population distribution based on migration rates (random based on data from Eastern/Western Germany case) and population
:: - Determine unemployment in the reunited country
:: - Determine suicide rates of North Koreans based on welfare / amount of underage persons (students) / average salary / amount of retired persons
:: - Determine new GDP based on above data (foreign investors being random)

:: '''Data sources:'''

:: Apart from the sources linked above, the data on North Korea will be used from CIA website [[https://www.cia.gov/library/publications/the-world-factbook/geos/kn.html]], comparable data on South Korea will be used from the same source for consistence [[https://www.cia.gov/librarY/publications/the-world-factbook/geos/ks.html]] and other specific data on South Korea will be pulled from Wikipedia.

:: ''The running simulation should show charts of the suicide rates, unemployment and GDP in time and the absolute numbers for the population distribution.''

:: Please let me know if this narrowing-down and breakdown is sufficient :) Thank you.

:: [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 00:48, 20 December 2018 (CET)

::: The relevance of comparison with Germany is questionable, but, ok. Let's say there perhaps isn't any better comparison. Nevertheless, I still don't understand, how the simulation should work. How the agents will act? How it will be measured? How you will be able to calculate all the figures? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:28, 21 December 2018 (CET)

:::: OK, I thought about how I would realize the simulation in NetLogo and I see you were right about it being too complicated. So I tried to simplify my model even more to be doable:
:::: - The patches will be divided proportionally by area of the two countries, they will also be characterized by a certain portion of the initial GDP as their wealth.
:::: - The turtles representing Koreans will have initial wealth (also based on the initial GDP) and they will be migrating towards one of the two states based on their inclination to migrate to the other country. This inclination will be calculated randomly based on the East-West Germany migration data and their wealth.
:::: - On each tick, the simulation will determine:
::::: - if the turtle (Korean) has a job (landed one, got fired, is working, or didn't get hired) based semi-randomly on the wealth of the patch the turtle is on.
::::: - The wealth of the patch and turtle -> if the turtle is employed, it gains wealth and also generates a little wealth for the patch; If unemployed, it drains the wealth of the patch a little and its wealth decreases a little.
::::: - Based on the suicide rates, employment and wealth, it will also semi-randomly decide if the person is likely to kill themselves.
:::: That way we can at least simulate and see the wealth distribution, suicide rates and population distribution in a very simplified model... Does that makes sense or am I still in over my head? :) [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 19:20, 21 December 2018 (CET)

::::: To be honest, I am a bit skeptical about the results. As the assignment is based on vague assumptions, I think the results will be very general. On the other hand, I appreciate the level of preparation, which is above average. Hence, it is exceptionally '''approved''' and I hope you invest the same level of effort into the simulation itself. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:52, 31 December 2018 (CET)
:::::: Thank you! [[User:Xkaij00|Xkaij00]] ([[User talk:Xkaij00|talk]]) 12:58, 31 December 2018 (CET)

== Simulation proposal (bobj00) ([[User:Bobrekjiri|Bobrekjiri]] ([[User talk:Bobrekjiri|talk]]) 13:49, 19 December 2018 (CET)) ''(Not approved yet)'' ==

Topic/goal: '''Comparing the efficiency of Diamond interchange and Diverging diamond interchange'''

'''Definition of the problem:''' 
- [https://en.wikipedia.org/wiki/Diverging_diamond_interchange Diverging diamond interchange] is an alternative to Diamond interchange that is being used in France since 1970s and was brought to light recently (2009) in USA because it should be more effective than Diamond interchange in terms of waiting times and also in terms of safety (fewer crossing points of traffic). 
- Goal of the simulation is to measure if the statement about lower waiting times is correct and under which conditions (traffic load, traffic lights setup). 
- Throughput and waiting times will be measured under several traffic conditions, for example: most cars exiting highway are heading south or most cars entering highway are heading west, etc. 
- Model does not include simulation of traffic accidents, so the safety cannot be measured and will not be part of the simulation. 

'''Simulation environment:''' Netlogo
'''Approved''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:29, 21 December 2018 (CET)

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== Simulation proposal [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 16:52, 19 December 2018 (CET) ==

Topic/goal: '''Maze runner vs fire'''

'''Definition of the problem:''' 
- There will be n apartment with rooms and obstacles (tables, bed, bath...), in a random room will be a people (user selects how many), who will try to find the way out, in some other random place will be fire spreading rapidly. Agents will not be able to move through walls and obstacles. The purpose of this simulation is to simulate an escape plan for an apartment.

'''Simulation environment''': Netlogo

: What is the purpose of the simulation? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:30, 21 December 2018 (CET)
:: to find out whether a person who is lost in a building will survive. Imagine yourself in a bulding you have never been before and a fire appears. Wouldn’t it be interesting to know If you would find your way out? [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 22:51, 21 December 2018 (CET)
::: It is just a modification of our Building escape example. Ok, it could be doable, but there must be a clear and substantial added value. Your assignment proposal must be much much more deeply elaborated. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 01:56, 31 December 2018 (CET)
:::: Ok, edited. [[User:Martin svejda|Martin svejda]] ([[User talk:Martin svejda|talk]]) 01:53, 3 January 2019 (CET)
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==Simulation proposal [[User:qnesa01|qnesa01]] ==

Topic/goal: '''Traffic simulation Argentinska street'''

'''Situation:''' 
- Argentinska street is one of the important roads in Prague that connects Bubenské nábřeží with bridge “Barikádníků”. It leads from city centre and other parts of city outside to the northern part of the country, and to Germany or Poland. Moreover, Argentinska street connects hospital “Na Bulovce” with city centre and other parts. For emergency vehicles it is the way how to get faster, where help is needed.

'''Definition of the problem:''' 
- There is traffic on the road during mornings and evenings, which makes people wait sometimes hours to get out and more important it makes difficult pass for emergency vehicles.

'''Purpose of simulation:''' 
In the scope is part of Argentinska street from Bubenské nábřeží till Dělnická street plus street Za Viaduktem, part of Jateční and part of Tusarova street as they have influence on the whole situation of Argentinska traffic. The purpose of the simulation is to find ways how to make traffic less. In order to do it will be checked, first, if it is possible to change lights more efficiently for cars flow. Second, answer the question – if we can add only one line only to one direction, which direction we have to choose: to city centre or from city centre?

'''Simulation environment''': Simprocess; SUMO (for traffic representation)

'''Brief process of simulation :''' 
1) Data collection. Data will be collected manually (observation) and from HERE traffic API. Manually for morning, midday and evening during 30 mins each part of the day within one week. At the end of data collecting the average distribution will be made based on the data.
2) Real situation simulation
3) Based on simulation of real situation will be checked the efficiency of lights changes
4) The hypothetical model of adding one more line will be created based on simulation of real situation
5) Summary

: Ok, SUMO could be used for this. I just don't understand what you will simulate in SUMO, and what you will simulate in Simprocess, and why? The combination of two tools is uneasy, so there should be a good reason. However sounds interesting. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:41, 21 December 2018 (CET)
: The Simprocess will be used for problem solution and SUMO for traffic representation of ready solution. Because SUMO does not have strong performance in searching solution, but very good for clear representation of ready result. Combination of two tools will be useful for this case. [[User:qnesa01|qnesa01]] ([[User talk:qnesa01|talk]]) 21:47, 27 December 2018 (CET)
:: Sorry, I still don't understand. Please, could you describe, how the simulation will look like in Simprocess and in SUMO? What will be the data you pass from SUMO to Simprocess (or vice versa)? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:36, 31 December 2018 (CET)

::: As I have mentioned above, firstly I am going to simulate initial state (as it is now). This will be done in Simprocess and SUMO. In Simprocess will be used variables: time of lights change, distribution of cars number arriving, staying and leaving. Based on same variables, simulation in SUMO will be created to get map based view. Secondly, I would like to work with variables to answer the proposed questions. All changes will be done first in Simprocess to get optimal solution. And then based again on the result values of variables from Simprocess the map view in SUMO will be made. So, SUMO will be used for representation purpose, to show Simprocess solution on the map. [[User:qnesa01|qnesa01]] ([[User talk:qnesa01|talk]]) 11:27, 3 January 2019 (CET)
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== Simulation proposal [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) ==

Topic/goal: '''Slime mold simulation (Reworked, Not Approved)''' 

'''Explanation:''' 
Slime mold (or more accurately physarum polycephalum) is a slime mold that inhabits shady, cool, moist areas,
such as decaying leaves and logs. Like slime molds in general, it is sensitive to light; in particular,
light can repel the slime mold and be a factor in triggering spore growth.

The interesting factor of this mold for my purpose of simulation is the smart-like path finding. This was
demonstrated by Harvard Magazine in a topic of solving a simple 2D maze, with finding the shortest path.
Also in another demonstration was proven, when the researchers place food at cities on the map, the fungus
collaborates, spreading out to map many possible configurations and then dying away to highlight the shortest
routes between cities and the most efficient overall system map. For more see: link (http://harvardmagazine.com/2010/05/networked-web-extra)

'''Definition of the problem:''' 
The ability to find the most effective route from one source of food to another is the key ability I'll be
using for my simulation. The behavior and the end result can be easily checked against the realistic data
provided from the recorded studies. The agents will be the mold unit itself, which is directly depended on
the neighbor agents and the environment. Parameters can be changed to create different environment and then
can be compared what would be the minimum strength/endurance + speed to according numbers of food sources.

'''Key parameters:'''

-number of "food" in the area (generated randomly)
-number of origin points of the slime mold (generated randomly)
-speed of spreading in which the mold is finding the food
-strength/endurance of the mold - the ability to survive without food (effectively it is the "searching range" of the mold)

'''Simulation environment''': Netlogo

: Reworked into more detailed version as requested. [[User:Kadj02|Kadj02]] ([[User talk:Kadj02|talk]]) 15:21, 7 January 2019 (CET)
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== Simulation proposal [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 22:33, 19 December 2018 (CET) ==

Topic/goal: '''Medieval Battle Simulation'''

'''Definition of the problem:''' 

Two kingdoms come to a dispute and after extensive diplomacy had failed, they take up arms and go to battle. 
Each kingdom can have different number of units, but they each choose from the same kind of units (unit types are better against some and weaker to other). 
Each side has their own staging area, but within that area the units can spawn at random locations to test different strategic formations. 
When they meet in battle, they fight to the last man who wins the dispute for his king.

'''Purpose of simulation:''' 
It simulates medieval combat on battlefield between two sides. 
The user can select which type of units and how many will each kingdom have. 
Repeated simulation can lead to conclusions on what strategy the kings should focus on and which units they should train for successful reign when facing a violent foe.

'''Simulation environment:''' NetLogo

: I would narrow this down to testing battle strategies. Forget kingdoms. You can perform a research on some historical strategies, their pros and cons, choose some, and try to simulate them, and compare. If it sounds meaningful, please, redefine the assignment. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:48, 21 December 2018 (CET)

:: The part about kingdoms was more of a story telling. The objects in NetLogo would just be the units (of different types). I envisioned them to spawn at random on their given side of the plane, but if it's necessary I could include spawning in historical formations. Would that be ok? [[User:Xlazl00|Xlazl00]] ([[User talk:Xlazl00|talk]]) 11:00, 22 December 2018 (CET)

::: The assignment is too brief to check. Please, define it in detail. Theoretically, the assignment should be the only source for you to solve it. It means that in this phase you should have thought out most of the details. Which formations you will simulate, how exactly should it look like, what will be the results, how you will evaluate it... [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:43, 31 December 2018 (CET)

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== Simulation proposal [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 09:30, 20 December 2018 (CET) ==

Topic/goal: '''Proof of a business plan - simulation of capacities of a Café'''

'''Definition of the problem:''' 

At the moment we have a venue in a small town under construction which we would like to turn into a café. 
The spatial dispositions are set and now there are many questions like: how to set up tables, find out how many people can be at one time in the café, if the café is profitable when the amount of people coming in is low/medium/high, etc. 

'''Purpose of simulation:''' 
As said, I would like to simulate a process of people coming in to find out the right amount of seats and tables when knowing there will be just one staff member at the time. 
I would also like to find out whether it is even possible to manage the whole place being just one person responsible for everything and/or whether it is cost efficient. 
 
The output data should help us find out whether the whole concept is viable and based on the findings we could adjust the business plan.

'''Simulation environment:''' I would like to use Simprocess for the simulation of the venue setting and probably complement it with some calculations in Excel.

: I like the idea, just hesitate about the tool. As far as I understand, a substantial part of the whole thing is about the spatial arrangement of the café. Then Simprocess is not the first choice. Why do you want to use it? [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 18:56, 21 December 2018 (CET)

::I liked that Simprocess allowed me to work with resources. And I see the tables and chairs as a resource, as well as the working power. If the flow of people coming in is well set up, I thought, by adjusting the resources, it should be possible to find out the optional setting. Do you propose any other tool to do that? I will be greatful for other ideas to improve the solution as it is a real problem we would like to solve. [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 10:21, 27 December 2018 (CET)

::: If you need to deal with spatial factors, NetLogo is definitely a better choice. If you omit the spatial characteristics, the simulation become trivial, what would not be enough for this paper. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 02:06, 31 December 2018 (CET)

:::: Ok, I can do the simulation in NetLogo and mind the spatial characteristics. I just thought the original idea was complex enought as it would put together several rather simple simulations and tasks - like finding out the right amount of visitors based on data from people that run cafés in different places (recalculating the number of visitors based on the wealthiness of the region, based on the capacity of the venue, the number of citizens and so on).
::::I believe I can go with netLogo for simulating the venue as well, although it is not completely clear now for me, how do I find out the right ammount of seats for example?
::::I can imagine a random movement of agents coming in taking a first not-taken seat. It can also be like the agent has a capacity (it can be group of 4 or just a pair or a single person visitor) and it could take the table/seat only in case there is enough space for the whole group. There could also be a quality parameters - like grading system for the seats - how far is it from the bar, is it near the toilet and so on. So yes, that might show that some places will be more popular then others. Also the agents might have a limit under which they dont go, like if they dont find a seat with quality high enough they will leave. Now when I am writing this down I think it might work although I still have some questions. Is this something you had in mind as well or am I on completely different track? Thanks. [[User:Xsmyt00|Xsmyt00]] ([[User talk:Xsmyt00|talk]]) 11:26, 31 December 2018 (CET)

::::: All right, now I understand it better. For the purpose you mentioned, Simprocess could be fine. The only problem is that the simulation itself is rather simple. Let's stick to it, nevertheless, I will require to make it really in detail including obtaining real data and simulating all relevant aspects. '''Approved.''' [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 21:58, 31 December 2018 (CET)

== Simulation proposal [[User:Manj01|Manj01]] ([[User talk:Manj01|talk]]) 15:21, 21 December 2018 (CET) ==

Topic/goal: '''Effective class configuration a plane between Prague and Dubai'''

'''Definition of the problem:''' 

There is a new airline operating between Prague and Dubai. The want to configure their planes as effectively as possible. They have one second hand Boeing 777 (396 seats in economy class only configuration)

'''Purpose of simulation:''' 
Company wants to operate daily air route between Prague and Dubai. The company can have up to four classes - economy, economy plus, business and first. Seat in higher class takes more space, but generates more money. Prices are available from companies currently operating on this route. Demand predictions can be made based on class configurations used by companies already operating on this and similar routes (6-hours mainly holiday) destinations.

'''Simulation environment:''' I would like to use MS Excel to do Monte Carlo simulation.

:: I just wonder, where is the randomnes, as you want to just derive the configuration from the already operating competition. If it should be a simulation, you would have to have real daily data (for reasonable long period, a year minimum) for the demand for the flights (there and back) and also for the individual classes. Only then you are able to derive probability distributions for the simulation that would make sense. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 22:31, 21 December 2018 (CET)

::: Ok, these are not available, so I will try a completely different idea:

Topic/goal: '''Archiving maximum efficiency in ticket management of a small company (real-life based data)'''

'''Definition of the problem:''' 

A small company has support personnel, testers and developers in one office. They together solve tickets created by customers. These tickets sometimes get stuck in ticketing system, because the numbers of people working there are not perfect. Campany uses Kayako and Jira to manage tickets - from these systems, there will be a lot of real-life data to base the simulation on.

'''Purpose of simulation:''' 
The simulation aims to provide the ideal amount of support people, testers/analysts and developers to solve tickets as quick as possible, while there are constraints, such as company budget and lowered effectivity of too many people working on the same ticket.

'''Simulation environment:''' I would like to use Simprocess to model and optimize the workflow.
: All right, '''approved''', but bear in mind that a detailed simulation based on real data is expected.

== Simulation proposal (xpipj04) ==

Topic/goal: You are what you eat

'''Definition of the problem:''' 
Most people nowadays want to hit the gym or eat healthy to get fit and at the same time take a long high quality sleep and work effectively. All the success in life and your energy comes from the food (nutrition values) you consume a day and the regime you have. The new year is knocking the door and you want to make sure that you will plan your food and regime effectively so your life is in balance.

'''Purpose of simulation:''' 
Based on the input you choose the simulation should be able to give you the expected levels of achieved energy, work efficiency and especially if you are about to get fit or you will drop down to be a couch potato.

'''Input parameters''' 
- Food consumed - listed types of food with calculated nutrition values (protein, fat, sugar, energy) 
- Time spent at gym (kardio, workout, culturist) 
- Time spent at work - type of work (manual, manager) 
- Time spent sleeping 

'''Output''' 
- Your BMI 
- Your fitness level 
- Your work focus 
- Your energy level 

'''Where I will get the data? ''' 
- My roommate is a nutrition specialist and member of huge fitness project so his advice will be the source of my dependencies between values as well as values for different types of nutrition. 
- Nutrition plans. 

'''How will I get the output?''' 
I would like to use NetLogo to be able to see both values (numbers) and also monthly progress on the display (maybe a characted running between job, eating and gym. Showing HP bar? :D).
If this kind of simulation is not suitable for NetLogo then Vensim? I have no idea how would I transfer the problem into equitations which are required.

:: You got it right - it is Vensim topic without any doubt. Without mathematical formulation you can not do any simulation, so you have to deal with mathematical model formulation anyway.So, if Vensim is ok with you, than we can approve it. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 08:20, 23 December 2018 (CET)
:::: Then I will go with Vensim and try to put together something meaningful! [[User:Jan.pippal|Jan Pippal]]
:::::: OK. Then '''approved'''. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 12:29, 24 December 2018 (CET)

Assignments WS 2018/2019

2018-12-21T22:36:34Z

Kadj02: /* Simulation proposal Kadj02 (talk) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) */

Assignments WS 2018/2019

2018-12-19T18:08:56Z

Kadj02: /* Simulation proposal (Kadj02 (talk) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) */

Assignments WS 2018/2019

2018-12-19T18:08:40Z

Kadj02: /* Simulation proposal Kadj02 (talk) (Jindřich Kadoun) 18:52, 19 December 2018 (CET) */

Assignments WS 2018/2019

2018-12-19T18:07:35Z

Kadj02: /* Simulation proposal Kadj02 (Jindřich Kadoun) (talk) 18:52, 19 December 2018 (CET) */

Assignments WS 2018/2019

2018-12-19T18:06:44Z

Kadj02:

Assignments WS 2018/2019

2018-12-19T18:05:29Z

Kadj02: