CoGames is a collection of multi-agent cooperative and competitive environments designed for reinforcement learning research. It serves as the game environment for the Alignment League Benchmark (ALB), a suite of multi-agent games to measure AI alignment, coordination, and collaboration. It currently features the 'Cogs vs Clips' game, offering environments for creating new games, training agents, and submitting them to the ALB leaderboard.
pip install cogamesVerified import paths — ran on the pinned version, not inferred.
This quickstart demonstrates how to install CoGames, list the available game missions, and then run a single episode of a mission using a simple random policy via the command-line interface. The CLI is the primary interaction method for CoGames.
Ensure your environment uses Python 3.12. Consider using `pyenv` or `conda` to manage Python versions. Refer to the PyPI `requires_python` field.
Familiarize yourself with the `cogames` CLI commands (`cogames missions`, `cogames play`, `cogames train`, `cogames upload`). For programmatic policy development, refer to the structure of `cogames.policy` modules.
Always use the `-o <filename.py>` flag with `cogames tutorial make-policy` to specify a new, unique filename and avoid accidental overwrites of your work.
Carefully review the `POLICY` specification format in the documentation. For simple cases, `random` or `class=cogames.policy.starter_agent.StarterPolicy` might suffice. For custom or trained policies, ensure the format `class=<your.module.MyPolicyClass> [data=/path/to/weights.safetensors] [kw.arg=value]` is correctly applied.