ABM of Physarum tranport networks
Example of emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on chemotaxis, the mobile agent population spontaneously forms dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained.
To run the model and get an nice animation as above :
run main.py
Parameter selection : in main.py you can select :
- board size
- initial trail map
- initial particule/agent map
- the model ( w or w/o collision)
- agent parameters (sensor and motor cf. model description in ref)
class.py is the model with collisions, only one particule per cell. class_free.py is the model freed from the collisions constrain.
- https://sagejenson.com/physarum
- Jones, J. (2010). Characteristics of pattern formation and evolution in approximations of physarum transport networks. Artificial Life, 16(2), 127-153. https://doi.org/10.1162/artl.2010.16.2.16202