{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2011:WI6Q3VLNF5XOF2D57POZGM7VB2","short_pith_number":"pith:WI6Q3VLN","canonical_record":{"source":{"id":"1112.2315","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2011-12-11T01:52:50Z","cross_cats_sorted":["cs.LG","cs.MA"],"title_canon_sha256":"1229f058f1257a96e9c2d5937a2d3c10a0e5dee2b874332f9f0602ad3d0f6a0b","abstract_canon_sha256":"d40252a6677d505e9cb2517ebea115f29bc3aadff212c3a1fa195a45f1377bd7"},"schema_version":"1.0"},"canonical_sha256":"b23d0dd56d2f6ee2e87dfbdd9333f50ebe2194af41277eefa4addd1ad90a9374","source":{"kind":"arxiv","id":"1112.2315","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1112.2315","created_at":"2026-05-18T04:06:34Z"},{"alias_kind":"arxiv_version","alias_value":"1112.2315v1","created_at":"2026-05-18T04:06:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1112.2315","created_at":"2026-05-18T04:06:34Z"},{"alias_kind":"pith_short_12","alias_value":"WI6Q3VLNF5XO","created_at":"2026-05-18T12:26:44Z"},{"alias_kind":"pith_short_16","alias_value":"WI6Q3VLNF5XOF2D5","created_at":"2026-05-18T12:26:44Z"},{"alias_kind":"pith_short_8","alias_value":"WI6Q3VLN","created_at":"2026-05-18T12:26:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2011:WI6Q3VLNF5XOF2D57POZGM7VB2","target":"record","payload":{"canonical_record":{"source":{"id":"1112.2315","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2011-12-11T01:52:50Z","cross_cats_sorted":["cs.LG","cs.MA"],"title_canon_sha256":"1229f058f1257a96e9c2d5937a2d3c10a0e5dee2b874332f9f0602ad3d0f6a0b","abstract_canon_sha256":"d40252a6677d505e9cb2517ebea115f29bc3aadff212c3a1fa195a45f1377bd7"},"schema_version":"1.0"},"canonical_sha256":"b23d0dd56d2f6ee2e87dfbdd9333f50ebe2194af41277eefa4addd1ad90a9374","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:06:34.834182Z","signature_b64":"AhGjX7MYJZk3mZtvp9Ef1CKTbyfkFzxMXl+vGITO+bKILVC5mbrwd6p5LGrfHDax6xQk+qdLO0HY0ehaNeKXCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b23d0dd56d2f6ee2e87dfbdd9333f50ebe2194af41277eefa4addd1ad90a9374","last_reissued_at":"2026-05-18T04:06:34.833294Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:06:34.833294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1112.2315","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T04:06:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8a5Zjwr+CgFUi7D6BZ+xi8ExEfClwDoRss9LSGeGnZHwlipTkOE7jR7hQqGosoCHZH1kxl58ifJX9KgnKHjTDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T10:20:12.173710Z"},"content_sha256":"0594dfebeb4289a1ac11431e3a63bbf7152825a21c9d7bc18f5a81122e22afc2","schema_version":"1.0","event_id":"sha256:0594dfebeb4289a1ac11431e3a63bbf7152825a21c9d7bc18f5a81122e22afc2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2011:WI6Q3VLNF5XOF2D57POZGM7VB2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptive Forgetting Factor Fictitious Play","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.MA"],"primary_cat":"stat.ML","authors_text":"David S. Leslie, Michalis Smyrnakis","submitted_at":"2011-12-11T01:52:50Z","abstract_excerpt":"It is now well known that decentralised optimisation can be formulated as a potential game, and game-theoretical learning algorithms can be used to find an optimum. One of the most common learning techniques in game theory is fictitious play. However fictitious play is founded on an implicit assumption that opponents' strategies are stationary. We present a novel variation of fictitious play that allows the use of a more realistic model of opponent strategy. It uses a heuristic approach, from the online streaming data literature, to adaptively update the weights assigned to recently observed a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1112.2315","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T04:06:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lMBfe9UhfW+5Hpd8mZ7MAU0az/XZzpa2/Li+ccKC0rKLMBQjeFZWIkkSw2io0KKFMc2zDfgz/KQ2NbqU1ZE+Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T10:20:12.174059Z"},"content_sha256":"5c9966fea175d0278136d23f3d4bf74752933f2e553a00468145f0f4b1779afe","schema_version":"1.0","event_id":"sha256:5c9966fea175d0278136d23f3d4bf74752933f2e553a00468145f0f4b1779afe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WI6Q3VLNF5XOF2D57POZGM7VB2/bundle.json","state_url":"https://pith.science/pith/WI6Q3VLNF5XOF2D57POZGM7VB2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WI6Q3VLNF5XOF2D57POZGM7VB2/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-01T10:20:12Z","links":{"resolver":"https://pith.science/pith/WI6Q3VLNF5XOF2D57POZGM7VB2","bundle":"https://pith.science/pith/WI6Q3VLNF5XOF2D57POZGM7VB2/bundle.json","state":"https://pith.science/pith/WI6Q3VLNF5XOF2D57POZGM7VB2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WI6Q3VLNF5XOF2D57POZGM7VB2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:WI6Q3VLNF5XOF2D57POZGM7VB2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"d40252a6677d505e9cb2517ebea115f29bc3aadff212c3a1fa195a45f1377bd7","cross_cats_sorted":["cs.LG","cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2011-12-11T01:52:50Z","title_canon_sha256":"1229f058f1257a96e9c2d5937a2d3c10a0e5dee2b874332f9f0602ad3d0f6a0b"},"schema_version":"1.0","source":{"id":"1112.2315","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1112.2315","created_at":"2026-05-18T04:06:34Z"},{"alias_kind":"arxiv_version","alias_value":"1112.2315v1","created_at":"2026-05-18T04:06:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1112.2315","created_at":"2026-05-18T04:06:34Z"},{"alias_kind":"pith_short_12","alias_value":"WI6Q3VLNF5XO","created_at":"2026-05-18T12:26:44Z"},{"alias_kind":"pith_short_16","alias_value":"WI6Q3VLNF5XOF2D5","created_at":"2026-05-18T12:26:44Z"},{"alias_kind":"pith_short_8","alias_value":"WI6Q3VLN","created_at":"2026-05-18T12:26:44Z"}],"graph_snapshots":[{"event_id":"sha256:5c9966fea175d0278136d23f3d4bf74752933f2e553a00468145f0f4b1779afe","target":"graph","created_at":"2026-05-18T04:06:34Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"It is now well known that decentralised optimisation can be formulated as a potential game, and game-theoretical learning algorithms can be used to find an optimum. One of the most common learning techniques in game theory is fictitious play. However fictitious play is founded on an implicit assumption that opponents' strategies are stationary. We present a novel variation of fictitious play that allows the use of a more realistic model of opponent strategy. It uses a heuristic approach, from the online streaming data literature, to adaptively update the weights assigned to recently observed a","authors_text":"David S. Leslie, Michalis Smyrnakis","cross_cats":["cs.LG","cs.MA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2011-12-11T01:52:50Z","title":"Adaptive Forgetting Factor Fictitious Play"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1112.2315","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0594dfebeb4289a1ac11431e3a63bbf7152825a21c9d7bc18f5a81122e22afc2","target":"record","created_at":"2026-05-18T04:06:34Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"d40252a6677d505e9cb2517ebea115f29bc3aadff212c3a1fa195a45f1377bd7","cross_cats_sorted":["cs.LG","cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2011-12-11T01:52:50Z","title_canon_sha256":"1229f058f1257a96e9c2d5937a2d3c10a0e5dee2b874332f9f0602ad3d0f6a0b"},"schema_version":"1.0","source":{"id":"1112.2315","kind":"arxiv","version":1}},"canonical_sha256":"b23d0dd56d2f6ee2e87dfbdd9333f50ebe2194af41277eefa4addd1ad90a9374","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b23d0dd56d2f6ee2e87dfbdd9333f50ebe2194af41277eefa4addd1ad90a9374","first_computed_at":"2026-05-18T04:06:34.833294Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T04:06:34.833294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AhGjX7MYJZk3mZtvp9Ef1CKTbyfkFzxMXl+vGITO+bKILVC5mbrwd6p5LGrfHDax6xQk+qdLO0HY0ehaNeKXCw==","signature_status":"signed_v1","signed_at":"2026-05-18T04:06:34.834182Z","signed_message":"canonical_sha256_bytes"},"source_id":"1112.2315","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0594dfebeb4289a1ac11431e3a63bbf7152825a21c9d7bc18f5a81122e22afc2","sha256:5c9966fea175d0278136d23f3d4bf74752933f2e553a00468145f0f4b1779afe"],"state_sha256":"79c4ae1e42077a35e2074999317af1ee6ccac3225fb457b2ba46bb142e7e802d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TcaAo5Sx8Sd7DMbjGMHQ+8bQN7saQcvjcoJQIoKVs36YjcsPE/QhJ3vmwbEwMFfN89l3ITQyd8OascsF2VLBDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T10:20:12.176124Z","bundle_sha256":"bff5a1dd0ab537e5f51b1caa2c3ea1959898394ffdeee21a7cb620638bb082dc"}}