facebookresearch/BenchMARL
BenchMARL is a library for benchmarking Multi-Agent Reinforcement Learning (MARL). BenchMARL allows to quickly compare different MARL algorithms, tasks, and models while being systematically grounded in its two core tenets: reproducibility and standardization.
Built on TorchRL as its execution backend, BenchMARL leverages Hydra for declarative, composable configuration management—enabling systematic hyperparameter sweeps and multi-run experiments across algorithm-task-model combinations. The library integrates with multiple environment ecosystems (VMAS, PettingZoo, MAgent2, SMACv2, MeltingPot) through a unified interface and outputs evaluation data compatible with marl-eval for statistically rigorous comparative analysis.
580 stars and 785 monthly downloads. Available on PyPI.
Stars
580
Forks
117
Language
Python
License
MIT
Category
Last pushed
Feb 07, 2026
Monthly downloads
785
Commits (30d)
0
Dependencies
6
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