{"adoption": {"forks": 411, "observed_at": "2026-08-28T04:06:27.176879+00:00", "stars": 2216}, "canonical_url": "https://ross.abutalabs.com/products/pymarl", "card": {"archived": false, "artifact_type": "framework", "description": "Python Multi-Agent Reinforcement Learning framework", "domain": ["reinforcement-learning", "machine-learning", "artificial-intelligence", "gaming-tools"], "enriched": true, "function": ["reinforcement-learning", "machine-learning", "agent-framework"], "health_score": 20, "homepage": null, "language": "Python", "license": "Apache-2.0", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["oxwhirl/pymarl"], "name": "oxwhirl/pymarl", "platform": ["python"], "pushed_at": "2022-12-08T02:58:39+00:00", "repo": "oxwhirl/pymarl", "stars": 2216, "tags": ["multi-agent-reinforcement-learning", "marl", "qmix", "coma", "vdn", "qtran", "smac", "starcraft-ii", "pytorch", "research", "linux", "docker", "gpu"], "topics": [], "urls": [], "use_cases": ["run multi-agent reinforcement learning experiments", "reproduce QMIX results on SMAC", "train cooperative multi-agent policies in StarCraft II", "compare value-decomposition MARL algorithms", "benchmark deep RL algorithms for multi-agent settings", "load and evaluate pretrained MARL checkpoints", "watch StarCraft II replays of trained agents"], "what_it_is": "PyMARL is WhiRL's PyTorch framework for deep multi-agent reinforcement learning, implementing algorithms such as QMIX, COMA, VDN, IQL, and QTRAN. It uses the SMAC StarCraft II environment for cooperative multi-agent experiments and supports Docker-based setup, model saving/loading, and replay generation.", "when_to_avoid": ["you need a maintained framework with recent updates or new algorithm support", "you want environments other than StarCraft II without extra integration work", "you need production deployment rather than research experimentation"], "when_to_choose": ["you need reference implementations of classic MARL algorithms like QMIX or COMA", "your research uses the SMAC StarCraft II benchmark", "you want a PyTorch codebase for multi-agent RL experiments"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/pymarl", "repo": "oxwhirl/pymarl", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:06:27.176879+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T02:45:57.420114+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cffb231b97487b4eac0622bbe064b22e62b8fc9c0310d1f4dc91f67230d11718", "fetched_at": "2026-08-28T04:06:27.176879+00:00", "kind": "readme", "missing": false, "url": "https://github.com/oxwhirl/pymarl"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2869, "days_push": 1364, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 32, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}