{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:EQCORJ2IJ5AYSUVIFGNGH76CP7","short_pith_number":"pith:EQCORJ2I","schema_version":"1.0","canonical_sha256":"2404e8a7484f418952a8299a63ffc27ff8f581cc65c26dafea89dfe620fa95ae","source":{"kind":"arxiv","id":"1907.05247","version":1},"attestation_state":"computed","paper":{"title":"An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"cs.AI","authors_text":"Jacob W. Crandall, Stefano V. Albrecht, Subramanian Ramamoorthy","submitted_at":"2019-07-10T09:47:44Z","abstract_excerpt":"Many multiagent applications require an agent to learn quickly how to interact with previously unknown other agents. To address this problem, researchers have studied learning algorithms which compute posterior beliefs over a hypothesised set of policies, based on the observed actions of the other agents. The posterior belief is complemented by the prior belief, which specifies the subjective likelihood of policies before any actions are observed. In this paper, we present the first comprehensive empirical study on the practical impact of prior beliefs over policies in repeated interactions. W"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1907.05247","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-07-10T09:47:44Z","cross_cats_sorted":["cs.MA"],"title_canon_sha256":"946db800c89ee9144ba7daa02c079b8b5eb834cba995345fd359ea147454e588","abstract_canon_sha256":"0ba95c22449b87bc804622b22edaac426a1022b9fb7e7e385c36d30692ff8645"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:51.035586Z","signature_b64":"meuHEwLL/Bp9WHZz5zwjTWAH730NPbcadDpNpfbDU3KWfFW66n+PessHIflO9KGCKNED56FT25kih+uppjDaDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2404e8a7484f418952a8299a63ffc27ff8f581cc65c26dafea89dfe620fa95ae","last_reissued_at":"2026-05-17T23:40:51.034913Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:51.034913Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"cs.AI","authors_text":"Jacob W. Crandall, Stefano V. Albrecht, Subramanian Ramamoorthy","submitted_at":"2019-07-10T09:47:44Z","abstract_excerpt":"Many multiagent applications require an agent to learn quickly how to interact with previously unknown other agents. To address this problem, researchers have studied learning algorithms which compute posterior beliefs over a hypothesised set of policies, based on the observed actions of the other agents. The posterior belief is complemented by the prior belief, which specifies the subjective likelihood of policies before any actions are observed. In this paper, we present the first comprehensive empirical study on the practical impact of prior beliefs over policies in repeated interactions. W"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.05247","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1907.05247","created_at":"2026-05-17T23:40:51.035002+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.05247v1","created_at":"2026-05-17T23:40:51.035002+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.05247","created_at":"2026-05-17T23:40:51.035002+00:00"},{"alias_kind":"pith_short_12","alias_value":"EQCORJ2IJ5AY","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_16","alias_value":"EQCORJ2IJ5AYSUVI","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_8","alias_value":"EQCORJ2I","created_at":"2026-05-18T12:33:15.570797+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/EQCORJ2IJ5AYSUVIFGNGH76CP7","json":"https://pith.science/pith/EQCORJ2IJ5AYSUVIFGNGH76CP7.json","graph_json":"https://pith.science/api/pith-number/EQCORJ2IJ5AYSUVIFGNGH76CP7/graph.json","events_json":"https://pith.science/api/pith-number/EQCORJ2IJ5AYSUVIFGNGH76CP7/events.json","paper":"https://pith.science/paper/EQCORJ2I"},"agent_actions":{"view_html":"https://pith.science/pith/EQCORJ2IJ5AYSUVIFGNGH76CP7","download_json":"https://pith.science/pith/EQCORJ2IJ5AYSUVIFGNGH76CP7.json","view_paper":"https://pith.science/paper/EQCORJ2I","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.05247&json=true","fetch_graph":"https://pith.science/api/pith-number/EQCORJ2IJ5AYSUVIFGNGH76CP7/graph.json","fetch_events":"https://pith.science/api/pith-number/EQCORJ2IJ5AYSUVIFGNGH76CP7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EQCORJ2IJ5AYSUVIFGNGH76CP7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EQCORJ2IJ5AYSUVIFGNGH76CP7/action/storage_attestation","attest_author":"https://pith.science/pith/EQCORJ2IJ5AYSUVIFGNGH76CP7/action/author_attestation","sign_citation":"https://pith.science/pith/EQCORJ2IJ5AYSUVIFGNGH76CP7/action/citation_signature","submit_replication":"https://pith.science/pith/EQCORJ2IJ5AYSUVIFGNGH76CP7/action/replication_record"}},"created_at":"2026-05-17T23:40:51.035002+00:00","updated_at":"2026-05-17T23:40:51.035002+00:00"}