{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:RKAKWJNL2EKKGYTF2Y6QCSASZW","short_pith_number":"pith:RKAKWJNL","schema_version":"1.0","canonical_sha256":"8a80ab25abd114a36265d63d014812cdb982bea94378207fdfdc1ef6cf6bea4f","source":{"kind":"arxiv","id":"1708.01791","version":1},"attestation_state":"computed","paper":{"title":"Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ole-Christoffer Granmo, Sondre Glimsdal","submitted_at":"2017-08-05T17:23:01Z","abstract_excerpt":"The multi-armed bandit problem forms the foundation for solving a wide range of on-line stochastic optimization problems through a simple, yet effective mechanism. One simply casts the problem as a gambler that repeatedly pulls one out of N slot machine arms, eliciting random rewards. Learning of reward probabilities is then combined with reward maximization, by carefully balancing reward exploration against reward exploitation. In this paper, we address a particularly intriguing variant of the multi-armed bandit problem, referred to as the {\\it Stochastic Point Location (SPL) Problem}. The ga"},"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":"1708.01791","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-08-05T17:23:01Z","cross_cats_sorted":[],"title_canon_sha256":"a4e9136298ef061fbb07a7bcf3db88d8060dadb48ac197b8af8e9f0642f10fd1","abstract_canon_sha256":"b8579e88bbbdc1255d51f41ad7886bf71ee07a03f26192c47460014eaffd1831"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:38:33.133557Z","signature_b64":"o6k31RJUmM1G+N7nNP1heyIOnrHiJRompGhmsR5y+Hryt6UIpaUS+tjPPtv0l6borsRlsHvXRKZ5B6qAIxqVAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8a80ab25abd114a36265d63d014812cdb982bea94378207fdfdc1ef6cf6bea4f","last_reissued_at":"2026-05-18T00:38:33.132976Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:38:33.132976Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Ole-Christoffer Granmo, Sondre Glimsdal","submitted_at":"2017-08-05T17:23:01Z","abstract_excerpt":"The multi-armed bandit problem forms the foundation for solving a wide range of on-line stochastic optimization problems through a simple, yet effective mechanism. One simply casts the problem as a gambler that repeatedly pulls one out of N slot machine arms, eliciting random rewards. Learning of reward probabilities is then combined with reward maximization, by carefully balancing reward exploration against reward exploitation. In this paper, we address a particularly intriguing variant of the multi-armed bandit problem, referred to as the {\\it Stochastic Point Location (SPL) Problem}. The ga"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01791","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":"1708.01791","created_at":"2026-05-18T00:38:33.133059+00:00"},{"alias_kind":"arxiv_version","alias_value":"1708.01791v1","created_at":"2026-05-18T00:38:33.133059+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01791","created_at":"2026-05-18T00:38:33.133059+00:00"},{"alias_kind":"pith_short_12","alias_value":"RKAKWJNL2EKK","created_at":"2026-05-18T12:31:39.905425+00:00"},{"alias_kind":"pith_short_16","alias_value":"RKAKWJNL2EKKGYTF","created_at":"2026-05-18T12:31:39.905425+00:00"},{"alias_kind":"pith_short_8","alias_value":"RKAKWJNL","created_at":"2026-05-18T12:31:39.905425+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/RKAKWJNL2EKKGYTF2Y6QCSASZW","json":"https://pith.science/pith/RKAKWJNL2EKKGYTF2Y6QCSASZW.json","graph_json":"https://pith.science/api/pith-number/RKAKWJNL2EKKGYTF2Y6QCSASZW/graph.json","events_json":"https://pith.science/api/pith-number/RKAKWJNL2EKKGYTF2Y6QCSASZW/events.json","paper":"https://pith.science/paper/RKAKWJNL"},"agent_actions":{"view_html":"https://pith.science/pith/RKAKWJNL2EKKGYTF2Y6QCSASZW","download_json":"https://pith.science/pith/RKAKWJNL2EKKGYTF2Y6QCSASZW.json","view_paper":"https://pith.science/paper/RKAKWJNL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1708.01791&json=true","fetch_graph":"https://pith.science/api/pith-number/RKAKWJNL2EKKGYTF2Y6QCSASZW/graph.json","fetch_events":"https://pith.science/api/pith-number/RKAKWJNL2EKKGYTF2Y6QCSASZW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RKAKWJNL2EKKGYTF2Y6QCSASZW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RKAKWJNL2EKKGYTF2Y6QCSASZW/action/storage_attestation","attest_author":"https://pith.science/pith/RKAKWJNL2EKKGYTF2Y6QCSASZW/action/author_attestation","sign_citation":"https://pith.science/pith/RKAKWJNL2EKKGYTF2Y6QCSASZW/action/citation_signature","submit_replication":"https://pith.science/pith/RKAKWJNL2EKKGYTF2Y6QCSASZW/action/replication_record"}},"created_at":"2026-05-18T00:38:33.133059+00:00","updated_at":"2026-05-18T00:38:33.133059+00:00"}