{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VQMYEWGYOQSZ5B4XUNPEJZ5Z2G","short_pith_number":"pith:VQMYEWGY","canonical_record":{"source":{"id":"2502.02133","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2025-02-04T09:06:07Z","cross_cats_sorted":["cs.AI","cs.LG","cs.SY"],"title_canon_sha256":"0f01309f3285a053bb78b48fd87bf88bb9d15557d677fa98d6aa5f3f48cf5710","abstract_canon_sha256":"a29130db88c04e031991b6ea9be59c3d74dccde83c6ed31b9e02f2f2231c8b16"},"schema_version":"1.0"},"canonical_sha256":"ac198258d874259e8797a35e44e7b9d18b721aedbda7e19dab152e077a576112","source":{"kind":"arxiv","id":"2502.02133","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02133","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02133v1","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02133","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_12","alias_value":"VQMYEWGYOQSZ","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_16","alias_value":"VQMYEWGYOQSZ5B4X","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_8","alias_value":"VQMYEWGY","created_at":"2026-07-05T10:09:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VQMYEWGYOQSZ5B4XUNPEJZ5Z2G","target":"record","payload":{"canonical_record":{"source":{"id":"2502.02133","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2025-02-04T09:06:07Z","cross_cats_sorted":["cs.AI","cs.LG","cs.SY"],"title_canon_sha256":"0f01309f3285a053bb78b48fd87bf88bb9d15557d677fa98d6aa5f3f48cf5710","abstract_canon_sha256":"a29130db88c04e031991b6ea9be59c3d74dccde83c6ed31b9e02f2f2231c8b16"},"schema_version":"1.0"},"canonical_sha256":"ac198258d874259e8797a35e44e7b9d18b721aedbda7e19dab152e077a576112","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:09:24.497567Z","signature_b64":"AS+hvxohSpG2U9IFODBC3Qp4l4RaJi601eWjz+2alRXTd8/Gzos3EiFoqLequ0V81VSxJe3ftMKeWbMV3halBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac198258d874259e8797a35e44e7b9d18b721aedbda7e19dab152e077a576112","last_reissued_at":"2026-07-05T10:09:24.497111Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:09:24.497111Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.02133","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":"2026-07-05T10:09:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g+u9/AEfD1XPClW3d5aP5zRrq9opUgAT1Xdhtpkftz3vKGkhNAdOCufAt8xCjbXZUvXcA69PM8/aejqhqwqMCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:49:18.875545Z"},"content_sha256":"248137336541087d5caf2d3c49ba1fd4ea2ba8a39f4a15efe4c26f635081001e","schema_version":"1.0","event_id":"sha256:248137336541087d5caf2d3c49ba1fd4ea2ba8a39f4a15efe4c26f635081001e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VQMYEWGYOQSZ5B4XUNPEJZ5Z2G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.SY"],"primary_cat":"eess.SY","authors_text":"Dirk Reinhardt, Florian Messerer, Jasper Hoffmann, Joschka Boedecker, Katrin Baumg\\\"artner, Moritz Diehl, Rudolf Reiter, Sebastien Gros, Shamburaj Sawant","submitted_at":"2025-02-04T09:06:07Z","abstract_excerpt":"The fields of MPC and RL consider two successful control techniques for Markov decision processes. Both approaches are derived from similar fundamental principles, and both are widely used in practical applications, including robotics, process control, energy systems, and autonomous driving. Despite their similarities, MPC and RL follow distinct paradigms that emerged from diverse communities and different requirements. Various technical discrepancies, particularly the role of an environment model as part of the algorithm, lead to methodologies with nearly complementary advantages. Due to thei"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02133","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/2502.02133/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":"2026-07-05T10:09:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K7zBmXuGeSeE7xApi630gwg69ufjXcAkdx+HCPpjeDP4Z/SPmQ18JbuCY2sD7Bf+OjgtnCxFAPZEDU9fepqNAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:49:18.876070Z"},"content_sha256":"199b32b504623ff14650a0fbe854b7bde03193c376aa206ea6a24387ce62edf1","schema_version":"1.0","event_id":"sha256:199b32b504623ff14650a0fbe854b7bde03193c376aa206ea6a24387ce62edf1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VQMYEWGYOQSZ5B4XUNPEJZ5Z2G/bundle.json","state_url":"https://pith.science/pith/VQMYEWGYOQSZ5B4XUNPEJZ5Z2G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VQMYEWGYOQSZ5B4XUNPEJZ5Z2G/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":"2026-08-03T17:49:18Z","links":{"resolver":"https://pith.science/pith/VQMYEWGYOQSZ5B4XUNPEJZ5Z2G","bundle":"https://pith.science/pith/VQMYEWGYOQSZ5B4XUNPEJZ5Z2G/bundle.json","state":"https://pith.science/pith/VQMYEWGYOQSZ5B4XUNPEJZ5Z2G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VQMYEWGYOQSZ5B4XUNPEJZ5Z2G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VQMYEWGYOQSZ5B4XUNPEJZ5Z2G","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":"a29130db88c04e031991b6ea9be59c3d74dccde83c6ed31b9e02f2f2231c8b16","cross_cats_sorted":["cs.AI","cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2025-02-04T09:06:07Z","title_canon_sha256":"0f01309f3285a053bb78b48fd87bf88bb9d15557d677fa98d6aa5f3f48cf5710"},"schema_version":"1.0","source":{"id":"2502.02133","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02133","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02133v1","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02133","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_12","alias_value":"VQMYEWGYOQSZ","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_16","alias_value":"VQMYEWGYOQSZ5B4X","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_8","alias_value":"VQMYEWGY","created_at":"2026-07-05T10:09:24Z"}],"graph_snapshots":[{"event_id":"sha256:199b32b504623ff14650a0fbe854b7bde03193c376aa206ea6a24387ce62edf1","target":"graph","created_at":"2026-07-05T10:09:24Z","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/2502.02133/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The fields of MPC and RL consider two successful control techniques for Markov decision processes. Both approaches are derived from similar fundamental principles, and both are widely used in practical applications, including robotics, process control, energy systems, and autonomous driving. Despite their similarities, MPC and RL follow distinct paradigms that emerged from diverse communities and different requirements. Various technical discrepancies, particularly the role of an environment model as part of the algorithm, lead to methodologies with nearly complementary advantages. Due to thei","authors_text":"Dirk Reinhardt, Florian Messerer, Jasper Hoffmann, Joschka Boedecker, Katrin Baumg\\\"artner, Moritz Diehl, Rudolf Reiter, Sebastien Gros, Shamburaj Sawant","cross_cats":["cs.AI","cs.LG","cs.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2025-02-04T09:06:07Z","title":"Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02133","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":"sha256:248137336541087d5caf2d3c49ba1fd4ea2ba8a39f4a15efe4c26f635081001e","target":"record","created_at":"2026-07-05T10:09:24Z","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":"a29130db88c04e031991b6ea9be59c3d74dccde83c6ed31b9e02f2f2231c8b16","cross_cats_sorted":["cs.AI","cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2025-02-04T09:06:07Z","title_canon_sha256":"0f01309f3285a053bb78b48fd87bf88bb9d15557d677fa98d6aa5f3f48cf5710"},"schema_version":"1.0","source":{"id":"2502.02133","kind":"arxiv","version":1}},"canonical_sha256":"ac198258d874259e8797a35e44e7b9d18b721aedbda7e19dab152e077a576112","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ac198258d874259e8797a35e44e7b9d18b721aedbda7e19dab152e077a576112","first_computed_at":"2026-07-05T10:09:24.497111Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:09:24.497111Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AS+hvxohSpG2U9IFODBC3Qp4l4RaJi601eWjz+2alRXTd8/Gzos3EiFoqLequ0V81VSxJe3ftMKeWbMV3halBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:09:24.497567Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.02133","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:248137336541087d5caf2d3c49ba1fd4ea2ba8a39f4a15efe4c26f635081001e","sha256:199b32b504623ff14650a0fbe854b7bde03193c376aa206ea6a24387ce62edf1"],"state_sha256":"f49aa301ddfbde2ad359dcb13ce8c5660dfcb8dc0d728dcc22ab843b6b6f57d9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M5zroPfBDJP3UJCU3qsOUStZgWEUqAWEnrOiEtyK4dSHweHNJ1W8eDgxSvtI4LRNe6hjdbD3Unsct1zKHcyrCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T17:49:18.881302Z","bundle_sha256":"9de0dfa6af82f620492f01cd5bb0b93523e99350ecbb072265b22b070b33a0a9"}}