{"as_of":"2026-08-21T09:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5674920e4316b7543a241dfbf97c0bc845a3fe7fece50c369a776cb06c22ab66","coverage":[{"denominator":146,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T23:56:00.724470Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.02091/citation-record","integrity":"/paper/2412.02091/integrity","json":"/paper/2412.02091/citation-record.json","paper":"/paper/2412.02091"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.337546Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.337546Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:1459bf9011bd92b052bee5cd4652116b31ed91f28144bbf8f31f0fa4cd054f26","observation_id":"6217f445-406e-44b4-a06d-54d2ceeb8f01","resolution":{"observed_at":"2026-08-11T23:56:00.337546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.342427Z","title":"A model of online misinformation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.342427Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:940c2d29fa26bc57edbbb83d8d32f71e9853ca44929a478e2df2128c4ce4f5da","observation_id":"6c85ce51-012a-467c-8064-bf73762d4e4b","resolution":{"observed_at":"2026-08-11T23:56:00.342427Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.346995Z","title":"The multiplicative weights updatemethod: ameta-algorithmandapplications","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.346995Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:07f2a70c5ad56055d880007c29c7c7a128c661f90b2b783af2fd3276920472ff","observation_id":"a1fffa89-d828-454b-adac-9f87c050b9eb","resolution":{"observed_at":"2026-08-11T23:56:00.346995Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.351316Z","title":"Deep reinforcement learning: A brief survey.IEEE Signal Processing Magazine, 34(6):26–38, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.351316Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:1a654c9601cc7e784c337c59e150f4f8bf767f2b852b88d37f6a02ef60f78914","observation_id":"6a198f9b-9f1a-43ef-92b3-df9b37d6d00d","resolution":{"observed_at":"2026-08-11T23:56:00.351316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.355692Z","title":"An efficient dynamic mechanism.Economet- rica, 81(6):2463–2485, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.355692Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:6dc6749c700242fc37f579cbc592289105224b5e2fde447e79f19dc6263cd165","observation_id":"adc18232-2d67-458d-8305-8aae9710d867","resolution":{"observed_at":"2026-08-11T23:56:00.355692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.359629Z","title":"Using confidence bounds for exploitation-exploration trade- offs","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.359629Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:b040d17a609f1fde6c338c421b9a40081676b629971e61d452ebdee087f062bd","observation_id":"affb08b9-945c-4c10-b7c0-72377086f379","resolution":{"observed_at":"2026-08-11T23:56:00.359629Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.364212Z","title":"The nonstochastic multiarmed bandit problem.SIAM Journal on Com- puting, 32(1):48–77, 2002","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.364212Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:ff448055e690664640d5ea870b5dcf24145b6b33edcac54d51b6e43f54a2f584","observation_id":"23e1bc6d-beef-4611-ac9b-63c33b908f4f","resolution":{"observed_at":"2026-08-11T23:56:00.364212Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.368304Z","title":"Correlated equilibrium as an expression of Bayesian rationality","venue":null,"work_id":null,"year":1987},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.368304Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:5cfc11f9162d371d3b16657c4096f78deafa85968fbc0ccfab8d5b411edce6ae","observation_id":"d691e754-5f9b-40ad-8f44-031399ce9f25","resolution":{"observed_at":"2026-08-11T23:56:00.368304Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.372307Z","title":"The emergence of cooperation among egoists.American Political Science Review, 75(2):306–318, 1981","venue":null,"work_id":null,"year":1981},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.372307Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:04bee33976cd4d76c0a38231e80ab6455efa8831f2dea0bbcccf97092f8f5d39","observation_id":"8aa510b6-94e2-4128-885c-0bdebbb46c8f","resolution":{"observed_at":"2026-08-11T23:56:00.372307Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.376120Z","title":"The Formula: The Universal Laws of Success","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.376120Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:25109c5e2910e21d3990cf8edef5aff8d80aab4d312743b6189c7aeb82d5597e","observation_id":"1ce94c58-1974-430b-8995-47379ed9790f","resolution":{"observed_at":"2026-08-11T23:56:00.376120Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.380923Z","title":"Dynamic incentives for congestion control","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.380923Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:b42199632cb26ca57fe1cc8313c4746e0850ae015db0bade20c24dd6ccbc1597","observation_id":"1cb87b26-b958-4b6a-b781-43887567c6ee","resolution":{"observed_at":"2026-08-11T23:56:00.380923Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.385172Z","title":"A neural probabilistic language model.J","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.385172Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:676b49520aa8c888b5dad6d4644212afb53d398d8ab2156a727dfbddbcd9e785","observation_id":"2bd0a905-a0f3-4799-a535-39ab03e0dae8","resolution":{"observed_at":"2026-08-11T23:56:00.385172Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.389340Z","title":"Taming the Matthew effect in online markets with social influence","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.389340Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:14832e9e89a18b5e056f0bc810450560e759a62c497668c87eeda8d8ddb79d65","observation_id":"280058df-b74d-447e-b414-a556cc22816c","resolution":{"observed_at":"2026-08-11T23:56:00.389340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.393254Z","title":"The dynamic pivot mechanism","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.393254Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:bb9fe8c7c4c34ecd8550d67d36d4dd0f88add36487969b406f081418029668ef","observation_id":"b0e9f2db-6e59-4e64-9874-2813c2813246","resolution":{"observed_at":"2026-08-11T23:56:00.393254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.397020Z","title":"Dynamic mechanism design: An introduction","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.397020Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:241d604c0730426c3cf3abad98bf6ce951050d9ca75dd007df280c5d9341021c","observation_id":"2ee5a282-4ee7-44ed-82a3-e57a9438f01c","resolution":{"observed_at":"2026-08-11T23:56:00.397020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.400660Z","title":"From external to internal regret.Jour- nal of Machine Learning Research, 8(6), 2007","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.400660Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:c2c466d5de1e11a4ca3d0b625e0e40d02402659a47cf4cb65ccf469985014a50","observation_id":"560cbd1e-87ca-40b5-8f2c-ddbabff06711","resolution":{"observed_at":"2026-08-11T23:56:00.400660Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.404299Z","title":"An Introduction to the Theory of Mechanism Design","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.404299Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:3bb0cc366c4bff4894c17c20492203e02a8097b7862595681f76ecc55d65964f","observation_id":"46cf5c75-9b58-49ab-baf8-da926974aaee","resolution":{"observed_at":"2026-08-11T23:56:00.404299Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.408171Z","title":"Superintelligence: Paths, Dangers, Strategies","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.408171Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:eee0c210d614627a7eea0b631baa932024fd316b246f38c66de9f11642c6396f","observation_id":"a69de65e-3f50-4729-8bd6-430d598feae9","resolution":{"observed_at":"2026-08-11T23:56:00.408171Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.411991Z","title":"Ethical issues in advanced artificial intelligence.Machine Ethics and Robot Ethics, pages 69–75, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.411991Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:4549e66b1b42ba90f2bf5460c714f1388747c657e475c5d100408c7486cbbb37","observation_id":"e395d10c-5de4-4fd6-b6c5-c7bf3e40bc55","resolution":{"observed_at":"2026-08-11T23:56:00.411991Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.415614Z","title":"Learn- ing to mitigate AI collusion on economic platforms.Advances in Neural Information Processing Systems, 35:37892–37904, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.415614Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:36efe5842ecc640a65e20ae55281941751793028758779ed9016d7e650e11588","observation_id":"7dc6ae90-b268-44db-802a-5d3415663f28","resolution":{"observed_at":"2026-08-11T23:56:00.415614Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.419499Z","title":"A survey of monte carlo tree search methods","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.419499Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:01b560f704d678ba522eb5b3c8ee554bbcb0e511b5b41e4f6916a19ff44e6352","observation_id":"6731de7f-a2ef-43a3-8e22-6874b91483ae","resolution":{"observed_at":"2026-08-11T23:56:00.419499Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.423612Z","title":"A comprehensive survey of graph embedding: Problems, techniques, and applications","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.423612Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:758eb0ae84b62ff4b323b030993c31fb8b90b57532e3049d45d28a7e0b58a1af","observation_id":"2285585f-da61-4f76-9bb1-1dd29e1d5abd","resolution":{"observed_at":"2026-08-11T23:56:00.423612Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.427413Z","title":"Artificial intelligence, algorithmic pricing, and collusion.American Economic Review, 110(10):3267–3297, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.427413Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:72e532b7deee5476ba0f076fbe2261cbd904f9f2b8957cfc4a9ee8390e3e1eae","observation_id":"72a1d687-08a5-48c9-a87b-e8e7b53c8a08","resolution":{"observed_at":"2026-08-11T23:56:00.427413Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.430984Z","title":"Self-predictive universal AI","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.430984Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:5f208408d8cb755598a8e9aa25bc9392033a5c1e78df9e768b160052692df485","observation_id":"ef6e43d6-345d-4334-b033-1770f70f3aad","resolution":{"observed_at":"2026-08-11T23:56:00.430984Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.434733Z","title":"Optimal coordi- nated planning amongst self-interested agents with private state","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.434733Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:dfbf5f42d2826c9b497fb7da178899d92acac0ab45cb7b3c08fee81cb3e4c392","observation_id":"10f84c2a-5ed3-458a-a767-21158954d741","resolution":{"observed_at":"2026-08-11T23:56:00.434733Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.438409Z","title":"Cambridge University Press, 2006","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.438409Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:355f7ccd112ece8c45086c9da28bec941c79fd541a8400239dc7133d70206c3f","observation_id":"c2f5f229-1533-49ce-9a68-c094b43ee44d","resolution":{"observed_at":"2026-08-11T23:56:00.438409Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.442224Z","title":"Evolu- tionary dynamics of biological auctions.Theoretical Population Biology, 81(1):69–80, 2012","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.442224Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:05a04c32796d81edd7f63545f01888e4fa47b537da2b9f9f87e2505ed345375d","observation_id":"6ba7a7c9-79a5-4aaa-b312-3422c562c94f","resolution":{"observed_at":"2026-08-11T23:56:00.442224Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.445778Z","title":"Dynamic pricing in a labor market: Surge pricing and flexible work on the Uber platform.Ec, 16:455, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.445778Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:b1350317910ac1a349df6fd1872af372e7b91641ca7b7db986ddacf0a387871e","observation_id":"def6f621-f15b-4cde-a4ee-dfdf52802156","resolution":{"observed_at":"2026-08-11T23:56:00.445778Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.449612Z","title":"Hedging in games: Faster convergence of external and swap regrets","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.449612Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:decef88bb6cb38edf1e2ab4614aa0320ed05557beaecf23b65a47135f88a06aa","observation_id":"95490cd0-bbe9-4d93-b545-557981afda60","resolution":{"observed_at":"2026-08-11T23:56:00.449612Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.453322Z","title":"Prediction with expert evaluators’ advice","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.453322Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:ad0d153e02bb28702e4ef6e7850172796de74ead52148e7128ada152486a04d8","observation_id":"203acd08-516f-4a6f-aabf-190a9e5352c5","resolution":{"observed_at":"2026-08-11T23:56:00.453322Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.457197Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.457197Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:0330ba609aa6d0280f399c2d4c43ae6e4a86053689f22a5143d6d176f9bc19b9","observation_id":"74c9e1e0-4da9-44ea-9868-575381d29cbc","resolution":{"observed_at":"2026-08-11T23:56:00.457197Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.460993Z","title":"A formulation of the simple theory of types.Journal of Symbolic Logic, 5:56–68, 1940","venue":null,"work_id":null,"year":1940},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.460993Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:ef84f236038653bd173d910ae3d0402d7f084f8f732a5e655b222653c249ea82","observation_id":"af3fdfba-3f9a-435e-ad48-fffda0e7bbe1","resolution":{"observed_at":"2026-08-11T23:56:00.460993Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.465002Z","title":"The problem of social cost.Journal of Law and Economics, 3(1):1–44, 1960","venue":null,"work_id":null,"year":1960},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.465002Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:b560237a70799f013697d42adeb36903f95eba6e8a504fcb09d996ad4b143e64","observation_id":"9e51077a-1b86-4b7d-88ba-9b1fe2b78c11","resolution":{"observed_at":"2026-08-11T23:56:00.465002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.469204Z","title":"The Firm, The Market, and The Law","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.469204Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:5b8a2d80465212b90880ae85f5e815b4b6803a2042fdd59d6b4c6c788ed93e67","observation_id":"bad48d59-e536-4348-9187-905218dc4bb2","resolution":{"observed_at":"2026-08-11T23:56:00.469204Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.473652Z","title":"Law for the platform economy.UCDL Rev., 51:133, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.473652Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:ae669ee6bcd329c172241cae46b9527885cc601d4a3c631ca419dcd78e429048","observation_id":"14d07d0f-4d7c-4348-b4eb-20bdda64d7c2","resolution":{"observed_at":"2026-08-11T23:56:00.473652Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10271","last_updated":"2024-06-04T14:34:38Z","snapshot_observed_at":"2026-08-16T14:00:38.756250Z","submitted_at":"2024-04-16T03:59:33Z","title":"Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.10271","snapshot_observed_at":"2026-08-11T23:56:00.477796Z","title":"Holliday, Bob M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.477796Z"},"links":{"cited_paper":"/paper/2404.10271","citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:6e1ef0f641cbb533e624313b8a10baca421186ea7ac681609383b24650cf12e5","observation_id":"9b1b5f03-b322-4923-9db5-96ade8787ba7","resolution":{"observed_at":"2026-08-11T23:56:00.477796Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.482424Z","title":"Cambridge University Press, 1996","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.482424Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:d81b5b2d7ca830af5836118da03996aac8880a31e3fde9b933d2d54a98dcff6d","observation_id":"1040dfd4-fb2e-47d2-b49c-f86e17fec938","resolution":{"observed_at":"2026-08-11T23:56:00.482424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.487015Z","title":"A collusion-proof dynamic mechanism.SSRN, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.487015Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:f34bd83ecf9e9980f875261a041eec0965a4c57ea138b539c3e560e4a7f4fd0a","observation_id":"dfe1b177-94ed-4836-bf51-1bf57c9e3842","resolution":{"observed_at":"2026-08-11T23:56:00.487015Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.490732Z","title":"From external to swap regret 2.0: An efficient reduction for large action spaces","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.490732Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:89228ad0226691a53c99d11efcf7737046d393b78b582b0aaf15552ddf34cfcc","observation_id":"aeb00fe9-64d9-4d83-ba29-e0b6742b049b","resolution":{"observed_at":"2026-08-11T23:56:00.490732Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.494693Z","title":"Logical and relational learning","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.494693Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:aab1ac9b9a51382cb6fc9931c954d9dd2e52a3ad327f21ff30b866affcbeeb0d","observation_id":"21e31179-4665-401c-a72c-6e029b107196","resolution":{"observed_at":"2026-08-11T23:56:00.494693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.498928Z","title":"The algorithmic foundations of differ- ential privacy.Found","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.498928Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:259c5574269f0d5b45111fa1baaa9465fcaacd10d6ce07808b91cc2e35124152","observation_id":"dd52d47f-66f4-4baa-b6c7-654cc86ef84e","resolution":{"observed_at":"2026-08-11T23:56:00.498928Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.502610Z","title":"Relational reinforce- ment learning","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.502610Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:cd465a9a1bf50b2a301c01dcd9c96c79d49dae5cf50adfcf76bed0b37fbedaf5","observation_id":"38e0b50d-1752-47d5-9fc5-08256f631efa","resolution":{"observed_at":"2026-08-11T23:56:00.502610Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.506290Z","title":"Matchmakers: the new economics of multisided platforms","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.506290Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:33dc13979a2eea4aaf8994d71ec6cf4db1b5aa763c57452f96d614b8166f57be","observation_id":"13ff3370-8792-4dde-bf84-71fa79b160a6","resolution":{"observed_at":"2026-08-11T23:56:00.506290Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.510011Z","title":"Reward tampering problems and solutions in reinforcement learning: A causal influence diagram perspective.Synthese, 198(Suppl 27):6435–6467, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.510011Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:e42a0652a74da15ec7b9e5260cd65ec91a5cd648c451cd5ceedbc6e971a2f607","observation_id":"eb6ba134-f45b-491a-bc13-78baf0cc78a4","resolution":{"observed_at":"2026-08-11T23:56:00.510011Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.513785Z","title":"Re- inforcement learning with a corrupted reward channel","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.513785Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:56c1f838c7a053b62f9c651ba06dbd0eb4cdfc91d82249229eec42882c86176c","observation_id":"4d6a5807-2c83-40d2-88cc-b473e0a49b8d","resolution":{"observed_at":"2026-08-11T23:56:00.513785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.517607Z","title":"AGI safety literature review","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.517607Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:bb2ce72ea3cf7bb6f565286dc04af5cd7f15498886e512cbf1973b6f66c43c99","observation_id":"f2698ef8-3976-4ce2-919c-ab6b274e234f","resolution":{"observed_at":"2026-08-11T23:56:00.517607Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.521276Z","title":"Reflective or- acles: A foundation for game theory in artificial intelligence","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.521276Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:797bd717113cb16b82bb604c4cd7ead6d0fe199bec2b1cd68f520212d3b3c7c5","observation_id":"6d12efec-3c2a-482d-a66d-65f02b08094a","resolution":{"observed_at":"2026-08-11T23:56:00.521276Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.524751Z","title":null,"venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.524751Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:86c7d8ed557135f8c4d2894e587b03e67b2911fa2134d4f58c861b78856ed28f","observation_id":"af5359bf-0782-4a28-9534-4ea34a1a7360","resolution":{"observed_at":"2026-08-11T23:56:00.524751Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.528481Z","title":"Economicsofoilrefining","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.528481Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:1888ae5b6b3c3a15b1a93c21aad4008f9b4e7e1f9a04dd864a6484d70389670b","observation_id":"89de71b5-c4ab-48e9-bd2d-400ce6c7618b","resolution":{"observed_at":"2026-08-11T23:56:00.528481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.532269Z","title":"Calibrated learning and correlated equilibrium","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.532269Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:67ed52f7389ca87da7db282a11fe374b9423161d4d905b1fb0894499388724c4","observation_id":"f806c2e4-c365-4690-8c6b-c00a10868aba","resolution":{"observed_at":"2026-08-11T23:56:00.532269Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.536357Z","title":"A decision-theoretic generalization of on-line learning and an application to boosting.Journal of Computer and System Sciences, 55(1):119–139, 1997","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.536357Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:9c6035e215a76e3d56ff3f7d116c4ef8d100e68cf35bbd9feafc9bd98d8b10a6","observation_id":"4f2752aa-76e0-415e-b201-1bd62ed557e8","resolution":{"observed_at":"2026-08-11T23:56:00.536357Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.540211Z","title":"Schapire, Yoram Singer, and Manfred K","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.540211Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:2a5ec3bdccafc6acf588b90c6e7e4b0b13aee849a09eccbf80cf0345c507a609","observation_id":"b0771398-efea-48b1-b9d7-531e99b07939","resolution":{"observed_at":"2026-08-11T23:56:00.540211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.544224Z","title":"The rationality of quali- fied lotteries","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.544224Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:56a1c21bdedc162d999c5d86c00eb697b5a469715fb3bb38393370752e5d9b3e","observation_id":"734e2856-1e38-410c-a609-1098d2f6a77a","resolution":{"observed_at":"2026-08-11T23:56:00.544224Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.548657Z","title":"MIT press, 1998","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.548657Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:241d61cad207e58847cf3c62cb449fd4bdb53b2f37f46eef348ebdd21805a599","observation_id":"b6f5f842-092b-46a6-9378-6393f88afd31","resolution":{"observed_at":"2026-08-11T23:56:00.548657Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.552194Z","title":"Artificial intelligence, values, and alignment.Minds and Machines, 30(3):411–437, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.552194Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:485c8c8a85f53eb9e60c2e75df7e4b0b07d4aea0a0c274da916c71b1551a2296","observation_id":"de4b3e6e-966d-4059-ad85-ee3b97f48593","resolution":{"observed_at":"2026-08-11T23:56:00.552194Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.556143Z","title":"Bayesian reinforcement learning: A survey","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.556143Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:c14961eca1d635e946bc98ecfd6ae53c9458cae616642870a723df2f01f30348","observation_id":"1f28048b-f2f6-4fb3-b9a2-ec7be43d61dd","resolution":{"observed_at":"2026-08-11T23:56:00.556143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.560057Z","title":"Graph embedding techniques, applica- tions, and performance: A survey.Knowledge-Based Systems, 151:78–94, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.560057Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:fef05fd1572b1943da627f16e142f9d12d68d728e59f769705da522772899135","observation_id":"7f2751a5-8bef-451a-84d0-5efda07364c3","resolution":{"observed_at":"2026-08-11T23:56:00.560057Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.563841Z","title":"Inconsistency of Bayesian in- ference for misspecified linear models, and a proposal for repairing it","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.563841Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:be607f1359a61b680ff11be922e45005e79263e68791efc71ff14d2f950722e1","observation_id":"3b7274ae-7134-4432-adfb-6fbd1d2749ff","resolution":{"observed_at":"2026-08-11T23:56:00.563841Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.568217Z","title":"The off-switch game","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.568217Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:0d3adfe8b62acec904e29f5bf0678ad0b4aa45b7ce6d3f1f9a2ad14bc8ee2010","observation_id":"32d209c2-436b-48a8-bb73-4da9b1458af9","resolution":{"observed_at":"2026-08-11T23:56:00.568217Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.572056Z","title":"Cooperative inverse reinforcement learning.Advances in Neural Informa- tion Processing Systems, 29, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.572056Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:fb7a2aa431146ecdabd51bb6b4414cca33aff53cb76f13bf8ee17ceeb83f5189","observation_id":"4ab5d993-fd02-4ff2-bef8-71e847ea15de","resolution":{"observed_at":"2026-08-11T23:56:00.572056Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.576001Z","title":"The tragedy of the commons","venue":null,"work_id":null,"year":1968},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.576001Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:ea251aad03edb73036c2171eb5c6781325e1da00dee0f3d8ede9c3be050f9d07","observation_id":"3de8e233-2243-4902-9b2b-afabaf3aae6b","resolution":{"observed_at":"2026-08-11T23:56:00.576001Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.579850Z","title":"Completeness in the theory of types.Journal of Symbolic Logic, 15(2):81–91, 1950","venue":null,"work_id":null,"year":1950},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.579850Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:6979843fd1cc29a9eb665dc44774e8a94eacbf817c3d5363e43fe50e5dc14be3","observation_id":"d0089685-5f65-4ff5-ac89-3132df8e7545","resolution":{"observed_at":"2026-08-11T23:56:00.579850Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.583839Z","title":"Tracking the best expert.Ma- chine learning, 32(2):151–178, 1998","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.583839Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:cdd8616ca7bc3db7d7b10b8f3cfae71ba1e2e565e364422ea00b5b738eefdcf6","observation_id":"241c5f4b-ba30-4405-8efa-f41aa3b0a07f","resolution":{"observed_at":"2026-08-11T23:56:00.583839Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.587304Z","title":"The many faces of exponentialweightsinonlinelearning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.587304Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:bcae69fe962ad263f636785ffd8a2f1f3c1aabd49506d25b1315213223914802","observation_id":"1c3e2999-b6e2-4642-be3a-2296dc69c0cc","resolution":{"observed_at":"2026-08-11T23:56:00.587304Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.591019Z","title":"The exponential mechanism for social welfare: Private, truthful, and nearly optimal","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.591019Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:961e70e7d28e65ac53d7cc6f5c231d038115db152d00933ea9ecadab84a05a74","observation_id":"ae6fca03-0fa4-45bf-8a8b-86ed41623d39","resolution":{"observed_at":"2026-08-11T23:56:00.591019Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.04898","last_updated":"2024-07-06T00:02:25Z","snapshot_observed_at":"2026-08-16T13:36:38.425638Z","submitted_at":"2024-07-06T00:02:25Z","title":"Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning","version":1},"cited_work":{"arxiv_id":"2407.04898","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.04898","snapshot_observed_at":"2026-08-11T23:56:01.205929Z","title":"Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning","venue":"cs.GT","work_id":"30fc0bd5-33d6-48ce-898a-6f9193c9ec54","year":2024},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.594642Z"},"links":{"cited_paper":"/paper/2407.04898","citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:e50c32ad146f7f493e75bae86c047913dce64abd6d541553fbb22b774ddceb2f","observation_id":"e41b946f-d2a9-4f18-aec3-8b8ba6e923ca","resolution":{"observed_at":"2026-08-11T23:56:01.211238Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.598968Z","title":"Universal Artificial Intelligence: Sequential Decisions based on Algorithmic Probability","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.598968Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:3f828fe10c4dfa828e88f1abdfdbbb7912d8a89c41f82e9c3c853e5f6e485958","observation_id":"d1af85ec-7077-43b8-a0eb-af19d41d7921","resolution":{"observed_at":"2026-08-11T23:56:00.598968Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.602602Z","title":"Feature reinforcement learning: Part I","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.602602Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:94060bf49d58f9de20c16135a118ec89dada1048764d9f80fcf41cf2152646eb","observation_id":"b2f60829-63bc-40e4-b756-836d44a65cc0","resolution":{"observed_at":"2026-08-11T23:56:00.602602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.175663Z","title":"CRC Press, 2024","venue":null,"work_id":"e7238ef8-9a83-4d63-bc45-a777ae008093","year":2024},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.606144Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:c2e260846a6983a119465484b15ff149c50af54b33c85695f8dfa45efe48e320","observation_id":"f2a59516-a8d6-4b10-bfa8-a10c41b4b133","resolution":{"observed_at":"2026-08-11T23:56:02.179729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.18074","last_updated":"2024-10-07T16:46:42Z","snapshot_observed_at":"2026-08-16T13:31:04.606847Z","submitted_at":"2024-07-25T14:28:58Z","title":"Principal-Agent Reinforcement Learning: Orchestrating AI Agents with Contracts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.18074","snapshot_observed_at":"2026-08-11T23:56:00.609953Z","title":"Principal-agent reinforcement learning: Orchestrating AI agents with contracts.arXiv preprint arXiv:2407.18074, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.609953Z"},"links":{"cited_paper":"/paper/2407.18074","citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:42e522636be02f14b976c4df58b4b64b3ca9ae73322683502622b19ea59eb6e8","observation_id":"593c4a24-bc2d-4fd1-b98c-b2ebc05da740","resolution":{"observed_at":"2026-08-11T23:56:00.609953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.162976Z","title":"Reward-free exploration for reinforcement learning","venue":null,"work_id":"a862280d-cec3-417a-9bf3-aa4c94a237fe","year":2020},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.614314Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:f9c5e7e2e1615e7710ac3580794c71724b3e784d62f3b97451bd4e52debde4da","observation_id":"dd15f004-c4c4-4f94-85d8-6503d780457d","resolution":{"observed_at":"2026-08-11T23:56:02.167275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.618166Z","title":"Provably efficient reinforcement learning with linear function approximation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.618166Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:5cefd65ae3705fd428a2447b503082db630741fca65c8430b8f62c58543f2229","observation_id":"542e3856-66cc-4f4d-82e6-50489218de5c","resolution":{"observed_at":"2026-08-11T23:56:00.618166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.143628Z","title":"Rational learning leads to Nash equilib- rium","venue":null,"work_id":"f2b3b9e2-6326-4b5a-b644-7d26317be74f","year":1993},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.621863Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:b0fa41ab675ab1fcbf16e0255b8aafdbb5684d5e77c31df4c265270bf0b7a3a3","observation_id":"1e1afb36-a4b4-488e-a518-f999dd481eaa","resolution":{"observed_at":"2026-08-11T23:56:02.147664Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.132944Z","title":"Gonzalez, Michael I","venue":null,"work_id":"91037181-dd7c-4e9d-9887-5dee237a87e2","year":2023},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.625666Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:96a11051e432d967d3d2b0ebf13b021dd3767fd8af667ac93fd8b661d60d3f91","observation_id":"3ced9075-2192-4b19-8c01-e9b52668bcca","resolution":{"observed_at":"2026-08-11T23:56:02.136678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.629715Z","title":"A survey of reinforcement learning from human feedback.arXiv:2312.14925, 10, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.629715Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:7c0ee81b9815bc1e8be2a1f2a47c29a4e883f6a5a2a0b7d01ed3f2b37f0c3ef0","observation_id":"a88ebf50-8c57-418b-8b0a-3a91b5bc9d8b","resolution":{"observed_at":"2026-08-11T23:56:00.629715Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.121112Z","title":"Mech- anism design in large games: Incentives and privacy","venue":null,"work_id":"0f3a37c6-4640-4cb7-80c1-b73be8540bed","year":2014},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.633577Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:f1dce24b8b5b092de3e4943873782874b407e1f331e8a72f4c50845bc10a0a62","observation_id":"f0429409-8cec-4ad5-9f34-5312f0368b9f","resolution":{"observed_at":"2026-08-11T23:56:02.125025Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.108084Z","title":"The rise of the platform economy","venue":null,"work_id":"20b33c76-4b74-4df9-98f4-f6eb39e59c2a","year":2016},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.637394Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:525905f11d143b6a6513f46d39e8fabf44e8fc13a5152feeb8800f3b88c0c176","observation_id":"6057d7ed-cf49-4855-9040-50dfabe934bf","resolution":{"observed_at":"2026-08-11T23:56:02.112429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.095591Z","title":"Bellman goes relational","venue":null,"work_id":"52a1530c-df4b-4be6-8397-745df6425632","year":2004},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.641048Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:73d9ea146da572d4f79805b30d0be4d87e2fd48c5120d5228d000be3ed8b0d77","observation_id":"40ec5578-7771-41e2-bb94-0d228b314f3d","resolution":{"observed_at":"2026-08-11T23:56:02.099661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.082544Z","title":"Bandit based monte-carlo planning","venue":null,"work_id":"17a2dc89-1cda-4a39-a3b1-788520030575","year":2006},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.644619Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:31dc823a33ab3f0020d455074d6df0fdfaf7da41135f4b2f86e1eb90e63f3fc1","observation_id":"f534922c-bb39-4664-9de3-d49fe285958d","resolution":{"observed_at":"2026-08-11T23:56:02.086990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.648645Z","title":"Paying to do better: Games with payments between learning agents.arXiv:2405.20880, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.648645Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:f455564122f9ae5423b1d84163265a43871bbe41f87ceba8fb631d18595b46a3","observation_id":"26c6102a-c9ae-43d8-8244-5ddc4813b053","resolution":{"observed_at":"2026-08-11T23:56:00.648645Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.069514Z","title":"Universal codes from switching strategies","venue":null,"work_id":"f6d21948-3eb5-4f3d-bcd2-a648554a7ef6","year":2013},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.652458Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:47a5f811614b0c596cad03774e1e777a4aa54c91c96f4c57df1df2cae336f3ac","observation_id":"e276eed5-bc61-4161-b383-cbbf2093d810","resolution":{"observed_at":"2026-08-11T23:56:02.073826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.056970Z","title":"Krichevsky and V","venue":null,"work_id":"ce1da1c0-d418-4560-8dba-ec699ad48371","year":2006},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.656358Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:09fd269610b2015909edb7f6726bca72e6e0df995bb449639b9dadcc7f70f411","observation_id":"456e641f-cee3-4c73-99f1-159d7fbdbec3","resolution":{"observed_at":"2026-08-11T23:56:02.061464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.044051Z","title":"A unified game-theoretic approach to multiagent reinforcement learning.Advances in Neural Information Processing Systems, 30, 2017","venue":null,"work_id":"db309515-ef01-4389-9a62-f5914d0b7c0f","year":2017},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.660262Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:419a37250ce96fdda932674f9cad6eb70f38dc8ccc5f146d86945a61f6639ac7","observation_id":"cb36b20f-8d48-4205-bf24-ad770218ee0a","resolution":{"observed_at":"2026-08-11T23:56:02.048431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:00.663954Z","title":"Bandit Algorithms","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.663954Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:62158db6f461e74009a6556e094fde866c4d2dac24f275dfe3ff7d9d635b451e","observation_id":"c8c05919-8918-4a19-a339-a7a62b1035c1","resolution":{"observed_at":"2026-08-11T23:56:00.663954Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.020152Z","title":"Thomp- son sampling is asymptotically optimal in general environments","venue":null,"work_id":"a8884936-52cf-456e-af82-852217ab2897","year":2016},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.667799Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:8e83a5a30d64aa01e6f8a5cf77852f26d49cf57d740de3e8344709071db45e42","observation_id":"25a13960-66f4-4ec6-bcb6-736074a9099c","resolution":{"observed_at":"2026-08-11T23:56:02.024580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:02.007490Z","title":"A formal solution to the grain of truth problem","venue":null,"work_id":"72a317e1-6685-4408-9e3a-2beb1c4d02f5","year":2016},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.671607Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:b5a80235f118dd2503f7a8301c820f34939a662318f8473caa2e84f0ac0d2858","observation_id":"8345c7a4-cec9-4623-9c03-e25ed384c392","resolution":{"observed_at":"2026-08-11T23:56:02.011678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.995231Z","title":"Walsh, and Michael L","venue":null,"work_id":"471b44f1-5eb1-4211-9fe2-62f57d038b62","year":2006},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.675744Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:6312e759ad154286ea2e53f3e89b01b26766dff9b194124502621e1a781a7201","observation_id":"e428798b-4a9b-4b95-87b0-bfaf050d9f62","resolution":{"observed_at":"2026-08-11T23:56:01.999348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.982159Z","title":"An Introduction to Kolmogorov Complexity and Its Applications","venue":null,"work_id":"34c94106-bd1f-4b58-b281-4986e4182fa1","year":2019},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.679584Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:ed33875bf27ff0a9b4f88f67fcfeb677d0d34dfca2bb4f2e47ca6ad81ee96fa5","observation_id":"1df2304d-fb51-411e-86a1-775d5095c3ed","resolution":{"observed_at":"2026-08-11T23:56:01.986452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.971283Z","title":"Markov games as a framework for multi-agent rein- forcement learning","venue":null,"work_id":"75ba0348-a0e1-4aaa-bef4-581379fb5e4e","year":1994},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.683289Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:0c37d8b525d5e89c96a6e11284be909010cd1d4435d71a753d5fb18218840396","observation_id":"e20590f9-ba97-4875-880b-7294ab2241d2","resolution":{"observed_at":"2026-08-11T23:56:01.975202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.959832Z","title":null,"venue":null,"work_id":"aac05b90-7e19-4aa6-8ca7-b5330099f9f3","year":2003},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.687209Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:260dba2864dcd828793a7344f0890f7336b06ef5f8b438bc0c32501aa532cbb2","observation_id":"181ee530-d9e1-4ce0-990a-21317afb815d","resolution":{"observed_at":"2026-08-11T23:56:01.963992Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.948514Z","title":"Lloyd and Kee Siong Ng","venue":null,"work_id":"dbd6de13-e6c3-40e9-8925-753651c324e1","year":2011},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.691113Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:ad78ff0448acdcdb166fa59f7d0a6a23f7800006e6d7ea9facbd7249dee14b99","observation_id":"a8a56564-3a59-4409-9d80-1c74351f735b","resolution":{"observed_at":"2026-08-11T23:56:01.952311Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.936641Z","title":"Pes- simism meets VCG: Learning dynamic mechanism design via offline rein- forcement learning","venue":null,"work_id":"73e2b02c-ef9b-44c0-a7cd-340db4375cdb","year":2022},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.694562Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:dae160e1779669e0024e4e654b171402145c831644c11eb55657f8c719ac2fda","observation_id":"13d86ac0-2ee9-4b2b-9153-1e27c224aa40","resolution":{"observed_at":"2026-08-11T23:56:01.940697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.924089Z","title":"Mechanism design via differential privacy","venue":null,"work_id":"9e00bbb5-f4d6-4018-a7ae-db3cd94433ff","year":2007},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.698198Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:6308657bce7612b2245844a494ae9850fb5da6da108b41115f8250856e4b75d6","observation_id":"2eb78945-7ed2-4e78-b17c-88f2a9763c59","resolution":{"observed_at":"2026-08-11T23:56:01.928234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.912136Z","title":"Kenneth Arrow’s last theorem.The Journal of Mechanism and Institution Design, 9(1):7–11, 2024","venue":null,"work_id":"d0677d3d-280d-4131-87ca-52e8107e7564","year":2024},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.702062Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:0fcb991014c951250156d3a4a86cd71f717aad354004556893bed09ed734df3c","observation_id":"b4fe5859-b4c2-4c27-a59f-862ef65d6c35","resolution":{"observed_at":"2026-08-11T23:56:01.916339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.900239Z","title":"Human-level control through deep re- inforcement learning","venue":null,"work_id":"e1d06c47-66ab-4dee-b5d5-9484bc004ab3","year":2015},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.705819Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:707e83014f26ab25c64e88263732991f0364c646d49c6cb8f78021ff6abadab1","observation_id":"8b8cd9ba-76a8-411e-92a0-51f5eb0b23bd","resolution":{"observed_at":"2026-08-11T23:56:01.904186Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.886520Z","title":"Efficient tracking of a growing number of experts","venue":null,"work_id":"c07f0b68-8635-40eb-8ba4-77b891d26b87","year":2017},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.709555Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:e8f8696a6f007d0e2136b22e468cef75590d6a53d171857478773ca6087c09bb","observation_id":"60fd1852-a849-474e-9128-7c669a8c1986","resolution":{"observed_at":"2026-08-11T23:56:01.891161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.872510Z","title":"Exploratory engineering in artificial intelligence","venue":null,"work_id":"d94e0e8a-9389-4228-83b9-a3cc061395ff","year":2014},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.713334Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:f8c0c57588aec96fcadc40a3bcd89d63d219404e86b74404435f436d0a711cd6","observation_id":"534956a3-9058-4f25-8a44-63ab8767111a","resolution":{"observed_at":"2026-08-11T23:56:01.877411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.858442Z","title":"Lloyd, and William Uther","venue":null,"work_id":"1460b7e5-d1c7-40df-a469-6fa4254cb8a1","year":2008},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.716871Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:855d8c959c445e842118b33b093e8699c563ae7124e6bad3c200d3d5f2017ca4","observation_id":"4c834a32-4dce-456e-8f78-af4041217695","resolution":{"observed_at":"2026-08-11T23:56:01.863052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.844491Z","title":"Feature re- inforcement learning in practice","venue":null,"work_id":"dbe7610b-5516-4f9d-9d85-a3d405955d8a","year":2011},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.720776Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:38970a32f651b6cc4fbe6a5125648a93a1062a5f24eedd36f16a8f0234aadcd5","observation_id":"1dfc2b30-6ea0-42a7-8fcc-37bfe1605a43","resolution":{"observed_at":"2026-08-11T23:56:01.849385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T23:56:01.832473Z","title":"Introduction to mechanism design (for computer scientist)","venue":null,"work_id":"d1efd71b-8fef-424c-aa25-0b9c8a3a98eb","year":2007},"citing_paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis","version":2},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-11T23:56:00.724470Z"},"links":{"citing_paper":"/paper/2412.02091"},"observation_digest":"sha256:1d475b5478db3aaab23007e552e1eb4ba8d3edf9ddb81efe7762bfd19fb34e6c","observation_id":"477810e9-3361-4bc2-a97e-0daadef4a59d","resolution":{"observed_at":"2026-08-11T23:56:01.836606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.02091","last_updated":"2025-04-13T01:25:54Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-15T00:45:55.929203Z","submitted_at":"2024-12-03T02:22:55Z","title":"The Problem of Social Cost in Multi-Agent General Reinforcement Learning: Survey and Synthesis"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":73,"verified_exact":1,"verified_fuzzy":26},"total_outbound_references":146},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 100 of 146 outbound references and 0 inbound Pith citation observations for arXiv:2412.02091."}