{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:22TNVOP5V32ACJUO3EDD2PE2UJ","short_pith_number":"pith:22TNVOP5","schema_version":"1.0","canonical_sha256":"d6a6dab9fdaef401268ed9063d3c9aa25af2ee2d4d7461313b67456445da443d","source":{"kind":"arxiv","id":"1404.4502","version":2},"attestation_state":"computed","paper":{"title":"A Complete Solver for Constraint Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.GT","authors_text":"Arnaud Lallouet, Thi-Van-Anh Nguyen","submitted_at":"2014-04-17T12:09:51Z","abstract_excerpt":"Game Theory studies situations in which multiple agents having conflicting objectives have to reach a collective decision. The question of a compact representation language for agents utility function is of crucial importance since the classical representation of a $n$-players game is given by a $n$-dimensional matrix of exponential size for each player. In this paper we use the framework of Constraint Games in which CSP are used to represent utilities. Constraint Programming --including global constraints-- allows to easily give a compact and elegant model to many useful games. Constraint Gam"},"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":"1404.4502","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2014-04-17T12:09:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1c4c26965ee091461cd61644fe1d20dac0c1d2ddbac672a292acf4396f335f22","abstract_canon_sha256":"bee8bdae28f0b546972b278384b94d8a0e08f37f6579b440db303dc29ce307ae"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:52:57.533780Z","signature_b64":"QlfThPlbX25EO2tLKgx75IrKbPWHN8EcRFMr9ricveSbdjKsnf137KjNt5tHN5nhvQN0p42XsOmw3kXeN4//DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6a6dab9fdaef401268ed9063d3c9aa25af2ee2d4d7461313b67456445da443d","last_reissued_at":"2026-05-18T02:52:57.533115Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:52:57.533115Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Complete Solver for Constraint Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.GT","authors_text":"Arnaud Lallouet, Thi-Van-Anh Nguyen","submitted_at":"2014-04-17T12:09:51Z","abstract_excerpt":"Game Theory studies situations in which multiple agents having conflicting objectives have to reach a collective decision. The question of a compact representation language for agents utility function is of crucial importance since the classical representation of a $n$-players game is given by a $n$-dimensional matrix of exponential size for each player. In this paper we use the framework of Constraint Games in which CSP are used to represent utilities. Constraint Programming --including global constraints-- allows to easily give a compact and elegant model to many useful games. Constraint Gam"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1404.4502","kind":"arxiv","version":2},"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":"1404.4502","created_at":"2026-05-18T02:52:57.533205+00:00"},{"alias_kind":"arxiv_version","alias_value":"1404.4502v2","created_at":"2026-05-18T02:52:57.533205+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1404.4502","created_at":"2026-05-18T02:52:57.533205+00:00"},{"alias_kind":"pith_short_12","alias_value":"22TNVOP5V32A","created_at":"2026-05-18T12:28:09.283467+00:00"},{"alias_kind":"pith_short_16","alias_value":"22TNVOP5V32ACJUO","created_at":"2026-05-18T12:28:09.283467+00:00"},{"alias_kind":"pith_short_8","alias_value":"22TNVOP5","created_at":"2026-05-18T12:28:09.283467+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/22TNVOP5V32ACJUO3EDD2PE2UJ","json":"https://pith.science/pith/22TNVOP5V32ACJUO3EDD2PE2UJ.json","graph_json":"https://pith.science/api/pith-number/22TNVOP5V32ACJUO3EDD2PE2UJ/graph.json","events_json":"https://pith.science/api/pith-number/22TNVOP5V32ACJUO3EDD2PE2UJ/events.json","paper":"https://pith.science/paper/22TNVOP5"},"agent_actions":{"view_html":"https://pith.science/pith/22TNVOP5V32ACJUO3EDD2PE2UJ","download_json":"https://pith.science/pith/22TNVOP5V32ACJUO3EDD2PE2UJ.json","view_paper":"https://pith.science/paper/22TNVOP5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1404.4502&json=true","fetch_graph":"https://pith.science/api/pith-number/22TNVOP5V32ACJUO3EDD2PE2UJ/graph.json","fetch_events":"https://pith.science/api/pith-number/22TNVOP5V32ACJUO3EDD2PE2UJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/22TNVOP5V32ACJUO3EDD2PE2UJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/22TNVOP5V32ACJUO3EDD2PE2UJ/action/storage_attestation","attest_author":"https://pith.science/pith/22TNVOP5V32ACJUO3EDD2PE2UJ/action/author_attestation","sign_citation":"https://pith.science/pith/22TNVOP5V32ACJUO3EDD2PE2UJ/action/citation_signature","submit_replication":"https://pith.science/pith/22TNVOP5V32ACJUO3EDD2PE2UJ/action/replication_record"}},"created_at":"2026-05-18T02:52:57.533205+00:00","updated_at":"2026-05-18T02:52:57.533205+00:00"}