{"data":{"full_name":"facebookresearch/BenchMARL","name":"BenchMARL","description":"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.","stars":580.0,"forks":117.0,"language":"Python","license":"MIT","archived":0.0,"subcategory":"game-playing-agents","last_pushed_at":"2026-02-07T16:00:29+00:00","pypi_package":"benchmarl","npm_package":null,"downloads_monthly":0.0,"dependency_count":6.0,"commits_30d":0.0,"reverse_dep_count":0.0,"maintenance_score":10.0,"adoption_score":10.0,"maturity_score":25.0,"community_score":24.0,"quality_score":69.0,"quality_tier":"established","risk_flags":"[]"},"meta":{"timestamp":"2026-04-11T13:45:28.494275+00:00"}}