Procedural Environment Generation for Accelerated Multi-Agent Reinforcement Learning
This repository depends on the mujoco-worldgen package. We provide a fork of this repository and thank the authors for their contribution. Install the necessary dependencies:
pip install -r worldgen/requirements.txt
pip install -e worldgen/
pip install -e maax/
Environment creation begins by defining an instance of the Base class. From there you can then add desired modules to introduce objects to the environment (Walls, Boxes, Ramps).
For adding environmental mechanics, we recommend implementing a new Wrapper inheriting from our custom Wrapper class designed for Multi-agent environments in Brax.
An example of environment creation can be found in the example.ipynb notebook. This notebook is currently parameterised to create a standard Hide-and_seek environment
with 2 hiders, 2 seekers, 2 boxes, 1 ramp and a small room sectioned by walls.