Simulation of ants colony in python

• an ant (called a "scout") travels more or less at random around the colony;
• if she discovers a food source she returns more or less directly to the nest, leaving a track of pheromones on her way;
• these pheromones being attractive, ants passing nearby will tend to follow, in a more or less direct way, this track;
• when they return to the nest, these same ants will strengthen the track;
• if two tracks are possible to reach the same food source, the shortest one will be covered by more ants at the same time than the long track;
• the short track will therefore be more and more reinforced, and therefore more and more attractive;
• the long track, it will eventually disappear, as pheromones are volatile;
• in the long term, all ants have therefore determined and "chosen" the shortest track.

The objective of this program is to reproduce in Python3 an algorithm that simulates ants' behaviour.

The simplest way - by default on "theory" mode:

python colony_ant_simulator.py

Use "reality" mode:

python colony_ant_simulator.py -m reality

Get help with option -h:

usage: Colony ant simulator [-h] [-m [{theory,reality}]] [n_ants]

Simulation of ants colony in python.

positional arguments:
  n_ants                Number of ants (recommended: 10-100; default: random number between 10 and 100)

options:
  -h, --help            show this help message and exit
  -m [{theory,reality}]
                        Simulation mode (default: "theory")

• Python 3.11
• coloraide