Difference between revisions of "Xkraj119"
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| − | + | ==Assignment== | |
| + | * Project name – Event Match-up Dynamics | ||
| + | * Author – Jan Kratochvíl | ||
| + | * Software used – NetLogo 5 | ||
| + | * Simulation type – Multi-agent model | ||
| + | == About the model == | ||
| + | The target of the demonstration is to simulate the match-up process as happens in a closed, limited-time, in-person event, such as a concert or a birthday party. | ||
| + | === The basic characteristics of the model are: === | ||
| + | * Every population member has two basic preference types – physical attraction and mental compatibility | ||
| + | * Every population member has a specific sex assigned, as well as a sexual preference – heterosexual, homosexual, bisexual, asexual | ||
| + | * The model is spatial. Population members interact with the nearest neighbors. After the interaction, they walk randomly until they find another actor. | ||
| + | * The length of interaction between population members (can be zero) is based on their mutual physical attraction | ||
| + | * After the interaction, both members score the other one. The score is a compound of physical attraction index and the mental compatibility index. The longer the interaction is, the more weight does the mental compatibility carries | ||
| + | * The resulting score is a basis for decision about mating. Some members have no intention of mating, yet take part in interactions | ||
| + | * The later it is in the game, the lower the score must be in order to be sufficient for mating | ||
| + | === Model configurability === | ||
| + | * Minimum score to match-up | ||
| + | * The pace with which does one’s standard lowers as the game reaches later stages | ||
| + | * Weight of physical attraction/mental compatibility in scoring model | ||
| + | * The initial spatial distribution of actors | ||
| + | == Goal variables == | ||
| + | * Median compatibility score of matched-up actors | ||
| + | * Median number of turns for a match-up to happen | ||
| + | * Median number of interaction it takes to reach a match-up | ||
| + | * Percentage of actors able to find a match-up | ||
| + | == Goals of the simulations are: == | ||
| + | * Does the initial spatial distribution of actors significantly alter the median compatibility score of matched-up actors | ||
| + | * What is the average of interactions needed to reach a match-up? | ||
| + | * Does altering the number of actors with no mating intention increase the percentage of actors able to find a match-up? | ||
| + | * How aggressively do need the actors’ standards need to lower in order for vast majority of actors to find a match-up? | ||
Revision as of 19:16, 19 December 2014
Contents
Assignment
- Project name – Event Match-up Dynamics
- Author – Jan Kratochvíl
- Software used – NetLogo 5
- Simulation type – Multi-agent model
About the model
The target of the demonstration is to simulate the match-up process as happens in a closed, limited-time, in-person event, such as a concert or a birthday party.
The basic characteristics of the model are:
- Every population member has two basic preference types – physical attraction and mental compatibility
- Every population member has a specific sex assigned, as well as a sexual preference – heterosexual, homosexual, bisexual, asexual
- The model is spatial. Population members interact with the nearest neighbors. After the interaction, they walk randomly until they find another actor.
- The length of interaction between population members (can be zero) is based on their mutual physical attraction
- After the interaction, both members score the other one. The score is a compound of physical attraction index and the mental compatibility index. The longer the interaction is, the more weight does the mental compatibility carries
- The resulting score is a basis for decision about mating. Some members have no intention of mating, yet take part in interactions
- The later it is in the game, the lower the score must be in order to be sufficient for mating
Model configurability
- Minimum score to match-up
- The pace with which does one’s standard lowers as the game reaches later stages
- Weight of physical attraction/mental compatibility in scoring model
- The initial spatial distribution of actors
Goal variables
- Median compatibility score of matched-up actors
- Median number of turns for a match-up to happen
- Median number of interaction it takes to reach a match-up
- Percentage of actors able to find a match-up
Goals of the simulations are:
- Does the initial spatial distribution of actors significantly alter the median compatibility score of matched-up actors
- What is the average of interactions needed to reach a match-up?
- Does altering the number of actors with no mating intention increase the percentage of actors able to find a match-up?
- How aggressively do need the actors’ standards need to lower in order for vast majority of actors to find a match-up?
