Simulation of semi-intelligent algae

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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: [1]

Problem definition

The algae works in two modes: food search and optimisation. The food search part involves the algae spreading in a outward pattern, until it finds a foodsource. When it succeeds, it optimizes 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.


Simulation is created using Netlogo 6.0.2.



The agents in our simulation are three by count.


Foods are agents that stand for foodbits in a petri dish. They are not found at first, until an algae steps on them by chance and sets their patch color from blue to green. This means that the food is now found. There is an exception however, the middle food is found from the beginning, as an inital food source for the living algae.


These agents are there to simulate algae spread. They dont simulate the whole area of the algae, that would be too expensive and inconvenient. Instead they stand as spreading tendrils of the algae. They color new patches yellow, which means the actual algae area. Their movement is random, although they only turn in random directions by 40°. This number seems to simulate the outward, radial pattern that the algae uses to find new food. It also creates nice veiny, fractal patterns.

They are hatched on green spots (the food that has been discovered). They have a limited time to live, whenever they step on a new non-yellow tile, it is lowered. This makes sure that there are no tendrils separated from the main body, just like in reality, separated algae cells would die without a food source.


Collectors are agents represented by blue arrows. Their task is to optimize the algae. They do so by travelling from food to food and increasing the popularity variable of each yellow patch they step on.



The setup button prepares the simulation environment. First the foods are distributed at preset coordinates. They are represented by static agents with their patch initially colored blue. Further foods can also be placed manually. Secondly the algae agents are hatched from the initial green food node and start their spread. Thirdly collectors are created at green spots as well.


to go

 make-collectors n-collectors
 make-algae physarums