Course material for the Multi-agents and computer graphics course. By the end of the course, you will create a traffic simulation, where each car is an individual agent that has to traverse a city with other cars:
Sample simulation created by Mateo Herrera, and Gerardo Gutiérrez.
The repository contains the following material:
- Documents: Has presentations, and cheat sheets.
- Agents Visualization: This is a webGL project that is used to visualize the random agents model using HTML instead of mesa.
- Mesa examples: The basic mesa examples. Included the random model, forest fire, and the city model.
- Install python. I strongly recommend using a custom venv or conda environment.
- I recommend miniconda over anaconda.
- There is a cheat sheet in the repo with all the conda commands.
- Either create a new environment with python (
conda create --name agents python), or use the provided environment file (conda env create -f agents_environment.yml)
- If you are using the python version on your sistem, or you created a new environment using venv, install the following packages:
- mesa:
pip install mesa - flask:
pip install flask
- mesa:
- By this moment, the environment will have all the packages needed for the projects and examples to run.