The Arcade Learning Environment ("ALE") is a widely used library in the reinforcement learning community that allows easy programmatic interfacing with Atari 2600 games, via the Stella emulator. We introduce a publicly available extension to the ALE that extends its support to multiplayer games and game modes. This interface is additionally integrated with PettingZoo to allow for a simple Gym-like interface in Python to interact with these games. We additionally introduce experimental baselines for all environments included.
Cite
@article{arxiv.2009.09341,
title = {Multiplayer Support for the Arcade Learning Environment},
author = {J. K. Terry and Benjamin Black and Luis Santos},
journal= {arXiv preprint arXiv:2009.09341},
year = {2021}
}