{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:VKAMWLJH7D6P2OPFSQNAOIDWHT","short_pith_number":"pith:VKAMWLJH","schema_version":"1.0","canonical_sha256":"aa80cb2d27f8fcfd39e5941a0720763cda6d0a1775f65f7353ddc3a19e2b7b6f","source":{"kind":"arxiv","id":"1709.09451","version":2},"attestation_state":"computed","paper":{"title":"Combining Prediction of Human Decisions with ISMCTS in Imperfect Information Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GT"],"primary_cat":"cs.MA","authors_text":"Moshe Bitan, Sarit Kraus","submitted_at":"2017-09-27T11:13:01Z","abstract_excerpt":"Monte Carlo Tree Search (MCTS) has been extended to many imperfect information games. However, due to the added complexity that uncertainty introduces, these adaptations have not reached the same level of practical success as their perfect information counterparts. In this paper we consider the development of agents that perform well against humans in imperfect information games with partially observable actions. We introduce the Semi-Determinized-MCTS (SDMCTS), a variant of the Information Set MCTS algorithm (ISMCTS). More specifically, SDMCTS generates a predictive model of the unobservable "},"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":"1709.09451","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MA","submitted_at":"2017-09-27T11:13:01Z","cross_cats_sorted":["cs.GT"],"title_canon_sha256":"d1d57aaa6214480fa438371bc8133386429e96d8664f862934dd9eed1f3d0abd","abstract_canon_sha256":"10185fcb91b87a8fc3daa734f6ae2b376cb9679ce18a53b1bba92d737a09c48c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:30:16.336249Z","signature_b64":"+t+k4+pPsXUR/xBdRT/zp31x+Oc1z3J9ghxwt5xKV4WD3x+RI2rbr2UIdNa6KAAmTUCR7gVVnzTmV4cybuLtCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa80cb2d27f8fcfd39e5941a0720763cda6d0a1775f65f7353ddc3a19e2b7b6f","last_reissued_at":"2026-05-18T00:30:16.335651Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:30:16.335651Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Combining Prediction of Human Decisions with ISMCTS in Imperfect Information Games","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GT"],"primary_cat":"cs.MA","authors_text":"Moshe Bitan, Sarit Kraus","submitted_at":"2017-09-27T11:13:01Z","abstract_excerpt":"Monte Carlo Tree Search (MCTS) has been extended to many imperfect information games. However, due to the added complexity that uncertainty introduces, these adaptations have not reached the same level of practical success as their perfect information counterparts. In this paper we consider the development of agents that perform well against humans in imperfect information games with partially observable actions. We introduce the Semi-Determinized-MCTS (SDMCTS), a variant of the Information Set MCTS algorithm (ISMCTS). More specifically, SDMCTS generates a predictive model of the unobservable "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.09451","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":"1709.09451","created_at":"2026-05-18T00:30:16.335772+00:00"},{"alias_kind":"arxiv_version","alias_value":"1709.09451v2","created_at":"2026-05-18T00:30:16.335772+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.09451","created_at":"2026-05-18T00:30:16.335772+00:00"},{"alias_kind":"pith_short_12","alias_value":"VKAMWLJH7D6P","created_at":"2026-05-18T12:31:49.984773+00:00"},{"alias_kind":"pith_short_16","alias_value":"VKAMWLJH7D6P2OPF","created_at":"2026-05-18T12:31:49.984773+00:00"},{"alias_kind":"pith_short_8","alias_value":"VKAMWLJH","created_at":"2026-05-18T12:31:49.984773+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/VKAMWLJH7D6P2OPFSQNAOIDWHT","json":"https://pith.science/pith/VKAMWLJH7D6P2OPFSQNAOIDWHT.json","graph_json":"https://pith.science/api/pith-number/VKAMWLJH7D6P2OPFSQNAOIDWHT/graph.json","events_json":"https://pith.science/api/pith-number/VKAMWLJH7D6P2OPFSQNAOIDWHT/events.json","paper":"https://pith.science/paper/VKAMWLJH"},"agent_actions":{"view_html":"https://pith.science/pith/VKAMWLJH7D6P2OPFSQNAOIDWHT","download_json":"https://pith.science/pith/VKAMWLJH7D6P2OPFSQNAOIDWHT.json","view_paper":"https://pith.science/paper/VKAMWLJH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1709.09451&json=true","fetch_graph":"https://pith.science/api/pith-number/VKAMWLJH7D6P2OPFSQNAOIDWHT/graph.json","fetch_events":"https://pith.science/api/pith-number/VKAMWLJH7D6P2OPFSQNAOIDWHT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VKAMWLJH7D6P2OPFSQNAOIDWHT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VKAMWLJH7D6P2OPFSQNAOIDWHT/action/storage_attestation","attest_author":"https://pith.science/pith/VKAMWLJH7D6P2OPFSQNAOIDWHT/action/author_attestation","sign_citation":"https://pith.science/pith/VKAMWLJH7D6P2OPFSQNAOIDWHT/action/citation_signature","submit_replication":"https://pith.science/pith/VKAMWLJH7D6P2OPFSQNAOIDWHT/action/replication_record"}},"created_at":"2026-05-18T00:30:16.335772+00:00","updated_at":"2026-05-18T00:30:16.335772+00:00"}