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Simulation of semi-intelligent algae

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.

A team of Japanese and Hungarian researchers have shown P. polycephalum can solve the Shortest path problem. When grown in a maze with oatmeal at two spots, P. polycephalum retracts from everywhere in the maze, except the shortest route connecting the two food sources. When presented with more than two food sources, P. polycephalum apparently solves a more complicated transportation problem. With more than two sources, the amoeba also produces efficient networks. In a 2010 paper, oatflakes were dispersed to represent Tokyo and 36 surrounding towns. P. polycephalum created a network similar to the existing train system, and "with comparable efficiency, fault tolerance, and cost".

This simulation should mimic the spread and path creation of the algae, as well as its ability to solve the shortest path problem.

[[Media:<iframe width="560" height="315" src="https://www.youtube.com/embed/HyzT5b0tNtk" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>]]

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