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A reimplementation of Schweitzer et al. 1996 as well as additional improvemnts for the Course Agent Based Modelling for Social Systems FS2023 ETH Zürich
22 Commits 2 Branches 0 Tags 119 KiB
Python 100%
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kaghog 61e92ae136 create function for ants to die and for nonlinear sensitivy function 
When ants hit a minimum sensitivy threshold (configurable), the ant is added to a dead list
and then removed from the model schedule and the environment in the model step.
The dead list is cleared every step

Nonlinear sensitivity using a logistic function is implemented.
2023-05-31 00:48:41 +02:00
agent.py create function for ants to die and for nonlinear sensitivy function 2023-05-31 00:48:41 +02:00
LICENSE Initial commit 2023-04-26 21:07:21 +02:00
main.py implemented test ant_follow_gradient, fixed step() function 2023-05-18 16:00:43 +02:00
model.py create function for ants to die and for nonlinear sensitivy function 2023-05-31 00:48:41 +02:00
multihex.py fix Grace's name 2023-05-17 15:57:23 +02:00
README.md add server visualization to README 2023-04-29 11:02:55 +02:00
server.py implemented test ant_follow_gradient, fixed step() function 2023-05-18 16:00:43 +02:00
shortlist.md add initial project files 2023-04-26 23:45:14 +02:00

README.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.