{"adoption": {"forks": 552, "observed_at": "2026-08-28T04:06:25.191690+00:00", "stars": 2196}, "canonical_url": "https://ross.abutalabs.com/products/deep-reinforcement-learning-papers", "card": {"archived": false, "artifact_type": "learning-resource", "description": "A list of recent papers regarding deep reinforcement learning", "domain": ["reinforcement-learning", "machine-learning", "artificial-intelligence", "tutorials"], "enriched": true, "function": ["documentation"], "health_score": 20, "homepage": null, "language": null, "license": null, "license_family": "other", "maturity": "abandoned", "member_repos": ["junhyukoh/deep-reinforcement-learning-papers"], "name": "junhyukoh/deep-reinforcement-learning-papers", "platform": ["cross-platform"], "pushed_at": "2016-06-15T16:32:20+00:00", "repo": "junhyukoh/deep-reinforcement-learning-papers", "stars": 2196, "tags": ["awesome-list", "papers", "deep-reinforcement-learning", "reading-list", "research"], "topics": [], "urls": [], "use_cases": ["find recent deep reinforcement learning papers", "reading list for learning deep RL", "survey papers on value-based and policy-based RL methods", "find RL papers on robotics and games", "discover papers on exploration and multi-agent RL"], "what_it_is": "A curated list of recent academic papers on deep reinforcement learning, organized into manually-defined bookmarks such as value methods, policy methods, robotics, games, and exploration. It is a static reading list sorted by time, not a software tool.", "when_to_avoid": ["you need runnable RL code or a library", "you want papers covering recent years beyond 2016", "you need tutorials or explanations rather than paper links"], "when_to_choose": ["you want a curated, categorized bibliography of deep RL papers", "you are surveying the 2015-2016 deep RL literature", "you need pointers to papers on specific RL subtopics like MCTS or inverse RL"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/deep-reinforcement-learning-papers", "repo": "junhyukoh/deep-reinforcement-learning-papers", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:06:25.191690+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T02:47:13.463961+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "6f1f9a849aa7c5abbf7b313984500c1aca85ca7b444d866d8f868d79b411aefd", "fetched_at": "2026-08-28T04:06:25.191690+00:00", "kind": "readme", "missing": false, "url": "https://github.com/junhyukoh/deep-reinforcement-learning-papers"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases", "no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 3990, "days_push": 3731, "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}}