{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:6CJSNUEZGO5D2SRPNVZCLFGP7Y","short_pith_number":"pith:6CJSNUEZ","canonical_record":{"source":{"id":"1207.1411","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2012-07-04T16:22:47Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c4a6ccdbbdd2301c37dbf6f02d3808ff775b663cf2ff8b5fbff6ab5c766d106c","abstract_canon_sha256":"8d29b1140bb4c3a363f72ad94dcbf71dc53ca4a3f707a9009d6e2f15dc22e976"},"schema_version":"1.0"},"canonical_sha256":"f09326d09933ba3d4a2f6d722594cffe08b7f2bd75a77085be4094f2d8034dc2","source":{"kind":"arxiv","id":"1207.1411","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1207.1411","created_at":"2026-05-18T03:51:37Z"},{"alias_kind":"arxiv_version","alias_value":"1207.1411v1","created_at":"2026-05-18T03:51:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1207.1411","created_at":"2026-05-18T03:51:37Z"},{"alias_kind":"pith_short_12","alias_value":"6CJSNUEZGO5D","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_16","alias_value":"6CJSNUEZGO5D2SRP","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_8","alias_value":"6CJSNUEZ","created_at":"2026-05-18T12:26:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:6CJSNUEZGO5D2SRPNVZCLFGP7Y","target":"record","payload":{"canonical_record":{"source":{"id":"1207.1411","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2012-07-04T16:22:47Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c4a6ccdbbdd2301c37dbf6f02d3808ff775b663cf2ff8b5fbff6ab5c766d106c","abstract_canon_sha256":"8d29b1140bb4c3a363f72ad94dcbf71dc53ca4a3f707a9009d6e2f15dc22e976"},"schema_version":"1.0"},"canonical_sha256":"f09326d09933ba3d4a2f6d722594cffe08b7f2bd75a77085be4094f2d8034dc2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:51:37.194808Z","signature_b64":"9TD+AqwXY38svl6+ZMtpMpDu+fG3yNK/Ci2b9jfHz1Ecrajy3DQzDyqOqBnCaZx9OTijEpi4EmQ1GERE3ByYCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f09326d09933ba3d4a2f6d722594cffe08b7f2bd75a77085be4094f2d8034dc2","last_reissued_at":"2026-05-18T03:51:37.194246Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:51:37.194246Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1207.1411","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":"2026-05-18T03:51:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h4DwoZw6xF7UlKpLWvMPxX9TrXwv7ONKNJfhAaggy5i6fcR/WFaHQmkZKENtUorou69rwsqVR/2xLWWyrdNtBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T06:23:03.070248Z"},"content_sha256":"6b9d42cfe2868e34d57aece1fb2ad3bb2cbfd52ba6e5ef2575a1244a0e6c3417","schema_version":"1.0","event_id":"sha256:6b9d42cfe2868e34d57aece1fb2ad3bb2cbfd52ba6e5ef2575a1244a0e6c3417"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:6CJSNUEZGO5D2SRPNVZCLFGP7Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayes' Bluff: Opponent Modelling in Poker","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.GT","authors_text":"Bryce Larson, Carmelo Piccione, Chris Rayner, Darse Billings, Finnegan Southey, Michael P. Bowling, Neil Burch","submitted_at":"2012-07-04T16:22:47Z","abstract_excerpt":"Poker is a challenging problem for artificial intelligence, with non-deterministic dynamics, partial observability, and the added difficulty of unknown adversaries. Modelling all of the uncertainties in this domain is not an easy task. In this paper we present a Bayesian probabilistic model for a broad class of poker games, separating the uncertainty in the game dynamics from the uncertainty of the opponent's strategy. We then describe approaches to two key subproblems: (i) inferring a posterior over opponent strategies given a prior distribution and observations of their play, and (ii) playin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1207.1411","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":"2026-05-18T03:51:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8YDxxOUsXn36R2GeVs0VeQXWVxHW6B8hS8Nk6tVs44m9om4aBoGA5yVZDtehkhfBZrfhmj/k1qa3SoXnk60aBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T06:23:03.070949Z"},"content_sha256":"94f32021903eac2c31d3bca1f370b527fb2b33e5d13185142d2d68ad3387f5a6","schema_version":"1.0","event_id":"sha256:94f32021903eac2c31d3bca1f370b527fb2b33e5d13185142d2d68ad3387f5a6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6CJSNUEZGO5D2SRPNVZCLFGP7Y/bundle.json","state_url":"https://pith.science/pith/6CJSNUEZGO5D2SRPNVZCLFGP7Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6CJSNUEZGO5D2SRPNVZCLFGP7Y/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":"2026-05-26T06:23:03Z","links":{"resolver":"https://pith.science/pith/6CJSNUEZGO5D2SRPNVZCLFGP7Y","bundle":"https://pith.science/pith/6CJSNUEZGO5D2SRPNVZCLFGP7Y/bundle.json","state":"https://pith.science/pith/6CJSNUEZGO5D2SRPNVZCLFGP7Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6CJSNUEZGO5D2SRPNVZCLFGP7Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:6CJSNUEZGO5D2SRPNVZCLFGP7Y","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":"8d29b1140bb4c3a363f72ad94dcbf71dc53ca4a3f707a9009d6e2f15dc22e976","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2012-07-04T16:22:47Z","title_canon_sha256":"c4a6ccdbbdd2301c37dbf6f02d3808ff775b663cf2ff8b5fbff6ab5c766d106c"},"schema_version":"1.0","source":{"id":"1207.1411","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1207.1411","created_at":"2026-05-18T03:51:37Z"},{"alias_kind":"arxiv_version","alias_value":"1207.1411v1","created_at":"2026-05-18T03:51:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1207.1411","created_at":"2026-05-18T03:51:37Z"},{"alias_kind":"pith_short_12","alias_value":"6CJSNUEZGO5D","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_16","alias_value":"6CJSNUEZGO5D2SRP","created_at":"2026-05-18T12:26:56Z"},{"alias_kind":"pith_short_8","alias_value":"6CJSNUEZ","created_at":"2026-05-18T12:26:56Z"}],"graph_snapshots":[{"event_id":"sha256:94f32021903eac2c31d3bca1f370b527fb2b33e5d13185142d2d68ad3387f5a6","target":"graph","created_at":"2026-05-18T03:51:37Z","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":"Poker is a challenging problem for artificial intelligence, with non-deterministic dynamics, partial observability, and the added difficulty of unknown adversaries. Modelling all of the uncertainties in this domain is not an easy task. In this paper we present a Bayesian probabilistic model for a broad class of poker games, separating the uncertainty in the game dynamics from the uncertainty of the opponent's strategy. We then describe approaches to two key subproblems: (i) inferring a posterior over opponent strategies given a prior distribution and observations of their play, and (ii) playin","authors_text":"Bryce Larson, Carmelo Piccione, Chris Rayner, Darse Billings, Finnegan Southey, Michael P. Bowling, Neil Burch","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2012-07-04T16:22:47Z","title":"Bayes' Bluff: Opponent Modelling in Poker"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1207.1411","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":"sha256:6b9d42cfe2868e34d57aece1fb2ad3bb2cbfd52ba6e5ef2575a1244a0e6c3417","target":"record","created_at":"2026-05-18T03:51:37Z","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":"8d29b1140bb4c3a363f72ad94dcbf71dc53ca4a3f707a9009d6e2f15dc22e976","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2012-07-04T16:22:47Z","title_canon_sha256":"c4a6ccdbbdd2301c37dbf6f02d3808ff775b663cf2ff8b5fbff6ab5c766d106c"},"schema_version":"1.0","source":{"id":"1207.1411","kind":"arxiv","version":1}},"canonical_sha256":"f09326d09933ba3d4a2f6d722594cffe08b7f2bd75a77085be4094f2d8034dc2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f09326d09933ba3d4a2f6d722594cffe08b7f2bd75a77085be4094f2d8034dc2","first_computed_at":"2026-05-18T03:51:37.194246Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:51:37.194246Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9TD+AqwXY38svl6+ZMtpMpDu+fG3yNK/Ci2b9jfHz1Ecrajy3DQzDyqOqBnCaZx9OTijEpi4EmQ1GERE3ByYCw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:51:37.194808Z","signed_message":"canonical_sha256_bytes"},"source_id":"1207.1411","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6b9d42cfe2868e34d57aece1fb2ad3bb2cbfd52ba6e5ef2575a1244a0e6c3417","sha256:94f32021903eac2c31d3bca1f370b527fb2b33e5d13185142d2d68ad3387f5a6"],"state_sha256":"c935c7d6c9f06ca90f07d21768de759bc91173b10a984103f5d75e54fb764a34"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gc67pI6Pnk0b0HRgu4mqSS6AncHnJ4JlclR5dYBHSgXoYDpQ6E5i3LIPYVMdBRDExY8iiwrmxajgMIGpt7mADw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T06:23:03.074150Z","bundle_sha256":"45ed218ab00fa315749018c96d849ba28c3eb97167cb8e0c517b3a2ce00faa3a"}}