A reimplementation of Schweitzer et al. 1996 as well as additional improvemnts for the Course Agent Based Modelling for Social Systems FS2023 ETH Zürich
AlexBocken
85f9ecdaec
We now have in main.py three functions to check theoretical decays vs actual decays. For this a custom testing environment is set up so no disruptions from for example, finding a food source or an ant depositing pheromones on the grid. The functions are otherwise pretty self-explanatory: check_pheromone_exponential_decay() check_ant_sensitivity_linear_decay() check_ant_pheromone_exponential_decay() Besides this, with this merge we also finally have an upper limit for ants on the grid using the num_max_agents model variable to check before new ants are generated. any use of the word 'chemical' has been replaced by 'pheromone' for consistency |
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agent.py | ||
LICENSE | ||
main.py | ||
model.py | ||
multihex.py | ||
README.md | ||
server.py | ||
shortlist.md |
ants
A reimplementation of Schweitzer et al. 1996 as well as additional improvemnts for the Course Agent Based Modelling for Social Systems FS2023 ETH Zürich
For the course Agent Based Modelling for Social Systems FS2023 we were tasked to implement a model of our own (in groups). For this, we decided to implement an enhanced version of Active random walkers simulate trunk trail formation by ants (Schweitzer et al. 1996) using Python and Mesa.
For now, wanted features can be found in our shortlist. For everything else start at main py
For a live visualization of the project you can execute server.py.