{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:VSP2Y6H2PD325Z3MQRMOH6REY6","short_pith_number":"pith:VSP2Y6H2","canonical_record":{"source":{"id":"2605.31388","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T14:52:12Z","cross_cats_sorted":[],"title_canon_sha256":"182c5159c001b4a4697dd7cb1dba1206d7e3bf922ae263b97e83fc6630307a25","abstract_canon_sha256":"a0fe1821bf0b712096ce49a3e8be61db4aab0bc99e8a40ce4d52465cc0922814"},"schema_version":"1.0"},"canonical_sha256":"ac9fac78fa78f7aee76c8458e3fa24c7a561df7c05d345ce0266ba2c126ab373","source":{"kind":"arxiv","id":"2605.31388","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.31388","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.31388v1","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.31388","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"pith_short_12","alias_value":"VSP2Y6H2PD32","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"pith_short_16","alias_value":"VSP2Y6H2PD325Z3M","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"pith_short_8","alias_value":"VSP2Y6H2","created_at":"2026-06-01T02:04:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:VSP2Y6H2PD325Z3MQRMOH6REY6","target":"record","payload":{"canonical_record":{"source":{"id":"2605.31388","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T14:52:12Z","cross_cats_sorted":[],"title_canon_sha256":"182c5159c001b4a4697dd7cb1dba1206d7e3bf922ae263b97e83fc6630307a25","abstract_canon_sha256":"a0fe1821bf0b712096ce49a3e8be61db4aab0bc99e8a40ce4d52465cc0922814"},"schema_version":"1.0"},"canonical_sha256":"ac9fac78fa78f7aee76c8458e3fa24c7a561df7c05d345ce0266ba2c126ab373","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T02:04:02.523149Z","signature_b64":"pMFg3DsktJPI75Pf69VnR9q3eVAYNLr1yjasUUforQlAIuP7Lj+18BfFOA9iJeSySxXw//VNqbcI/9rNB76iBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac9fac78fa78f7aee76c8458e3fa24c7a561df7c05d345ce0266ba2c126ab373","last_reissued_at":"2026-06-01T02:04:02.522441Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T02:04:02.522441Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.31388","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-01T02:04:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9ur13ex9YynnWlLF5mpgtAIxYJg4G6ZuHSJb1SEStQ9W7EVWDudCWmGGDUl70BfV3bO9ykBN5Kwss6SLivERDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T14:02:43.894547Z"},"content_sha256":"260167104808fd92cb987ce548fa32716a953c8d90cc8b70f3e5e61fe86f9726","schema_version":"1.0","event_id":"sha256:260167104808fd92cb987ce548fa32716a953c8d90cc8b70f3e5e61fe86f9726"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:VSP2Y6H2PD325Z3MQRMOH6REY6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Constrained Multi-Objective Reinforcement Learning with Max-Min Criterion","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Amir Leshem, Giseung Park, Hyunyoung Nam, Woohyeon Byeon, Youngchul Sung","submitted_at":"2026-05-29T14:52:12Z","abstract_excerpt":"Multi-Objective Reinforcement Learning (MORL) extends standard RL by optimizing policies with respect to multiple, often conflicting, objectives. While max-min MORL has emerged as an effective approach for promoting fairness, its applicability remains limited, particularly when constraints must be incorporated. In this paper, we propose a MORL framework that integrates the max-min criterion with explicit constraint satisfaction. We establish a theoretical foundation for the proposed framework and validate the resulting algorithm through convergence analysis and experiments in tabular settings."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.31388","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.31388/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":"2026-06-01T02:04:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fge7XXUuPGGkLDEwNKG077c8bGLJMnAK+6qDNflm1zz9r7HkpzJsh9mutW+O5sm93DiJLK3Rmzd1lrBvGE9tAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T14:02:43.894920Z"},"content_sha256":"77f0be44b00f34970cc6f32fccdaa005dd24324fdb200a55ad3c0e126df66d77","schema_version":"1.0","event_id":"sha256:77f0be44b00f34970cc6f32fccdaa005dd24324fdb200a55ad3c0e126df66d77"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VSP2Y6H2PD325Z3MQRMOH6REY6/bundle.json","state_url":"https://pith.science/pith/VSP2Y6H2PD325Z3MQRMOH6REY6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VSP2Y6H2PD325Z3MQRMOH6REY6/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":"2026-06-30T14:02:43Z","links":{"resolver":"https://pith.science/pith/VSP2Y6H2PD325Z3MQRMOH6REY6","bundle":"https://pith.science/pith/VSP2Y6H2PD325Z3MQRMOH6REY6/bundle.json","state":"https://pith.science/pith/VSP2Y6H2PD325Z3MQRMOH6REY6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VSP2Y6H2PD325Z3MQRMOH6REY6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:VSP2Y6H2PD325Z3MQRMOH6REY6","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":"a0fe1821bf0b712096ce49a3e8be61db4aab0bc99e8a40ce4d52465cc0922814","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T14:52:12Z","title_canon_sha256":"182c5159c001b4a4697dd7cb1dba1206d7e3bf922ae263b97e83fc6630307a25"},"schema_version":"1.0","source":{"id":"2605.31388","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.31388","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.31388v1","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.31388","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"pith_short_12","alias_value":"VSP2Y6H2PD32","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"pith_short_16","alias_value":"VSP2Y6H2PD325Z3M","created_at":"2026-06-01T02:04:02Z"},{"alias_kind":"pith_short_8","alias_value":"VSP2Y6H2","created_at":"2026-06-01T02:04:02Z"}],"graph_snapshots":[{"event_id":"sha256:77f0be44b00f34970cc6f32fccdaa005dd24324fdb200a55ad3c0e126df66d77","target":"graph","created_at":"2026-06-01T02:04:02Z","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/2605.31388/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-Objective Reinforcement Learning (MORL) extends standard RL by optimizing policies with respect to multiple, often conflicting, objectives. While max-min MORL has emerged as an effective approach for promoting fairness, its applicability remains limited, particularly when constraints must be incorporated. In this paper, we propose a MORL framework that integrates the max-min criterion with explicit constraint satisfaction. We establish a theoretical foundation for the proposed framework and validate the resulting algorithm through convergence analysis and experiments in tabular settings.","authors_text":"Amir Leshem, Giseung Park, Hyunyoung Nam, Woohyeon Byeon, Youngchul Sung","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T14:52:12Z","title":"Constrained Multi-Objective Reinforcement Learning with Max-Min Criterion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.31388","kind":"arxiv","version":1},"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":"sha256:260167104808fd92cb987ce548fa32716a953c8d90cc8b70f3e5e61fe86f9726","target":"record","created_at":"2026-06-01T02:04:02Z","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":"a0fe1821bf0b712096ce49a3e8be61db4aab0bc99e8a40ce4d52465cc0922814","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T14:52:12Z","title_canon_sha256":"182c5159c001b4a4697dd7cb1dba1206d7e3bf922ae263b97e83fc6630307a25"},"schema_version":"1.0","source":{"id":"2605.31388","kind":"arxiv","version":1}},"canonical_sha256":"ac9fac78fa78f7aee76c8458e3fa24c7a561df7c05d345ce0266ba2c126ab373","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ac9fac78fa78f7aee76c8458e3fa24c7a561df7c05d345ce0266ba2c126ab373","first_computed_at":"2026-06-01T02:04:02.522441Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T02:04:02.522441Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pMFg3DsktJPI75Pf69VnR9q3eVAYNLr1yjasUUforQlAIuP7Lj+18BfFOA9iJeSySxXw//VNqbcI/9rNB76iBQ==","signature_status":"signed_v1","signed_at":"2026-06-01T02:04:02.523149Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.31388","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:260167104808fd92cb987ce548fa32716a953c8d90cc8b70f3e5e61fe86f9726","sha256:77f0be44b00f34970cc6f32fccdaa005dd24324fdb200a55ad3c0e126df66d77"],"state_sha256":"5c8856a320d84d88872044589d5ad33dc882b9c4592a9a4e7a6b08bc444727c0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"32pQnj4mT2J+wyffbtiMUQnkYQckf346jS++P3J8uMSETXNBfmNwrMuI6RP95z9iSTQQU8UrLmGDeQIJ4FtHAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T14:02:43.896827Z","bundle_sha256":"737be555f5eacef0a8fd9c356c12c95a18b69752457a0fa866abb6f579f32044"}}