{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:UCAE6QYG67EJ5BHWDZTR5JW5NW","short_pith_number":"pith:UCAE6QYG","canonical_record":{"source":{"id":"1912.03517","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-07T15:19:22Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9324b4ac5151db7bf28b97cef6b39703cdb279e26564b96ee63f8ee5e24e6fc0","abstract_canon_sha256":"9031e78a165e63e59ad40af6b054ba0b4fcb3e62e10a23c58cff835555252568"},"schema_version":"1.0"},"canonical_sha256":"a0804f4306f7c89e84f61e671ea6dd6db20188c9f63340c59181464a9fa440bd","source":{"kind":"arxiv","id":"1912.03517","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.03517","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"arxiv_version","alias_value":"1912.03517v3","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.03517","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"pith_short_12","alias_value":"UCAE6QYG67EJ","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"pith_short_16","alias_value":"UCAE6QYG67EJ5BHW","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"pith_short_8","alias_value":"UCAE6QYG","created_at":"2026-07-05T01:27:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:UCAE6QYG67EJ5BHWDZTR5JW5NW","target":"record","payload":{"canonical_record":{"source":{"id":"1912.03517","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-07T15:19:22Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9324b4ac5151db7bf28b97cef6b39703cdb279e26564b96ee63f8ee5e24e6fc0","abstract_canon_sha256":"9031e78a165e63e59ad40af6b054ba0b4fcb3e62e10a23c58cff835555252568"},"schema_version":"1.0"},"canonical_sha256":"a0804f4306f7c89e84f61e671ea6dd6db20188c9f63340c59181464a9fa440bd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:27:20.222961Z","signature_b64":"vJgdlPr4wBIKXQK8oK3+FFh4eB09iNWcB1BLs27JMIo1Ly1I96B77n7sYhiJcmbFQZByZD4owiD8mdkfzVcOCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a0804f4306f7c89e84f61e671ea6dd6db20188c9f63340c59181464a9fa440bd","last_reissued_at":"2026-07-05T01:27:20.222550Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:27:20.222550Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.03517","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:27:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"75MEQY48UxR9gdgf0RliZteIvZFYFPLygbC11U7KxB6wYIobs3mB+VjR0l9v8Jv5Xpx3BZIglQEQIVXm8HRFBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T03:46:04.641242Z"},"content_sha256":"314b0fa47ad143a62f4be2427afe9bb36558ed05495bf13223c3743d03ff7ad4","schema_version":"1.0","event_id":"sha256:314b0fa47ad143a62f4be2427afe9bb36558ed05495bf13223c3743d03ff7ad4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:UCAE6QYG67EJ5BHWDZTR5JW5NW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"No-Regret Exploration in Goal-Oriented Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Alessandro Lazaric, Evrard Garcelon, Jean Tarbouriech, Matteo Pirotta, Michal Valko","submitted_at":"2019-12-07T15:19:22Z","abstract_excerpt":"Many popular reinforcement learning problems (e.g., navigation in a maze, some Atari games, mountain car) are instances of the episodic setting under its stochastic shortest path (SSP) formulation, where an agent has to achieve a goal state while minimizing the cumulative cost. Despite the popularity of this setting, the exploration-exploitation dilemma has been sparsely studied in general SSP problems, with most of the theoretical literature focusing on different problems (i.e., fixed-horizon and infinite-horizon) or making the restrictive loop-free SSP assumption (i.e., no state can be visit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.03517","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1912.03517/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T01:27:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ww43WsV0a9uZx7j9915sgmrXYZAChIUAdIO8Fwqym6mVIyIibDTkuRuztFqS1YrJPZqC1B4AOEIyYYtRvTpxDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T03:46:04.641627Z"},"content_sha256":"876204a254e2b12001a7c5e6896c6b70b981fe8c21c3dfd0b2bd3bc38d2b9a6e","schema_version":"1.0","event_id":"sha256:876204a254e2b12001a7c5e6896c6b70b981fe8c21c3dfd0b2bd3bc38d2b9a6e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UCAE6QYG67EJ5BHWDZTR5JW5NW/bundle.json","state_url":"https://pith.science/pith/UCAE6QYG67EJ5BHWDZTR5JW5NW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UCAE6QYG67EJ5BHWDZTR5JW5NW/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":"2026-07-08T03:46:04Z","links":{"resolver":"https://pith.science/pith/UCAE6QYG67EJ5BHWDZTR5JW5NW","bundle":"https://pith.science/pith/UCAE6QYG67EJ5BHWDZTR5JW5NW/bundle.json","state":"https://pith.science/pith/UCAE6QYG67EJ5BHWDZTR5JW5NW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UCAE6QYG67EJ5BHWDZTR5JW5NW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:UCAE6QYG67EJ5BHWDZTR5JW5NW","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":"9031e78a165e63e59ad40af6b054ba0b4fcb3e62e10a23c58cff835555252568","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-07T15:19:22Z","title_canon_sha256":"9324b4ac5151db7bf28b97cef6b39703cdb279e26564b96ee63f8ee5e24e6fc0"},"schema_version":"1.0","source":{"id":"1912.03517","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.03517","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"arxiv_version","alias_value":"1912.03517v3","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.03517","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"pith_short_12","alias_value":"UCAE6QYG67EJ","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"pith_short_16","alias_value":"UCAE6QYG67EJ5BHW","created_at":"2026-07-05T01:27:20Z"},{"alias_kind":"pith_short_8","alias_value":"UCAE6QYG","created_at":"2026-07-05T01:27:20Z"}],"graph_snapshots":[{"event_id":"sha256:876204a254e2b12001a7c5e6896c6b70b981fe8c21c3dfd0b2bd3bc38d2b9a6e","target":"graph","created_at":"2026-07-05T01:27:20Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1912.03517/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Many popular reinforcement learning problems (e.g., navigation in a maze, some Atari games, mountain car) are instances of the episodic setting under its stochastic shortest path (SSP) formulation, where an agent has to achieve a goal state while minimizing the cumulative cost. Despite the popularity of this setting, the exploration-exploitation dilemma has been sparsely studied in general SSP problems, with most of the theoretical literature focusing on different problems (i.e., fixed-horizon and infinite-horizon) or making the restrictive loop-free SSP assumption (i.e., no state can be visit","authors_text":"Alessandro Lazaric, Evrard Garcelon, Jean Tarbouriech, Matteo Pirotta, Michal Valko","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-07T15:19:22Z","title":"No-Regret Exploration in Goal-Oriented Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.03517","kind":"arxiv","version":3},"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":"sha256:314b0fa47ad143a62f4be2427afe9bb36558ed05495bf13223c3743d03ff7ad4","target":"record","created_at":"2026-07-05T01:27:20Z","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":"9031e78a165e63e59ad40af6b054ba0b4fcb3e62e10a23c58cff835555252568","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-12-07T15:19:22Z","title_canon_sha256":"9324b4ac5151db7bf28b97cef6b39703cdb279e26564b96ee63f8ee5e24e6fc0"},"schema_version":"1.0","source":{"id":"1912.03517","kind":"arxiv","version":3}},"canonical_sha256":"a0804f4306f7c89e84f61e671ea6dd6db20188c9f63340c59181464a9fa440bd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a0804f4306f7c89e84f61e671ea6dd6db20188c9f63340c59181464a9fa440bd","first_computed_at":"2026-07-05T01:27:20.222550Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:27:20.222550Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vJgdlPr4wBIKXQK8oK3+FFh4eB09iNWcB1BLs27JMIo1Ly1I96B77n7sYhiJcmbFQZByZD4owiD8mdkfzVcOCw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:27:20.222961Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.03517","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:314b0fa47ad143a62f4be2427afe9bb36558ed05495bf13223c3743d03ff7ad4","sha256:876204a254e2b12001a7c5e6896c6b70b981fe8c21c3dfd0b2bd3bc38d2b9a6e"],"state_sha256":"82daa87512af35840e24d56100036e0b8b7e48eb05f23de874e7423f2a1e83a5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ae2Z6hBBPjj9SlJAD18yAReLbuOx5yl3bZ1458yeoNkqV5kYTLwl4qoO2sDEy4+jPt6y0VO2pCYE5F3jpvybAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T03:46:04.643499Z","bundle_sha256":"b1850abed61703c8b04c50cab41b6ccf3dfab78cf54f0a2d4868b1b4c44e52de"}}