{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:NQ2WAUY4CF2YYZ5B32TIWDIJZH","short_pith_number":"pith:NQ2WAUY4","canonical_record":{"source":{"id":"2001.10122","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-27T23:37:41Z","cross_cats_sorted":["cs.MA","math.OC","stat.ML"],"title_canon_sha256":"419827408279cb59e4c8dd0fdd5a9c44f045d1e1bf8fe8ce26e162b20391932d","abstract_canon_sha256":"4f11fee009b16e9b207ec163e394acb67d90bd3903be95dde69f57482f1087fb"},"schema_version":"1.0"},"canonical_sha256":"6c3560531c11758c67a1dea68b0d09c9e7f09b85004121dd120ef8b3877fdb4d","source":{"kind":"arxiv","id":"2001.10122","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.10122","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"arxiv_version","alias_value":"2001.10122v1","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.10122","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"pith_short_12","alias_value":"NQ2WAUY4CF2Y","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"pith_short_16","alias_value":"NQ2WAUY4CF2YYZ5B","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"pith_short_8","alias_value":"NQ2WAUY4","created_at":"2026-07-05T00:36:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:NQ2WAUY4CF2YYZ5B32TIWDIJZH","target":"record","payload":{"canonical_record":{"source":{"id":"2001.10122","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-27T23:37:41Z","cross_cats_sorted":["cs.MA","math.OC","stat.ML"],"title_canon_sha256":"419827408279cb59e4c8dd0fdd5a9c44f045d1e1bf8fe8ce26e162b20391932d","abstract_canon_sha256":"4f11fee009b16e9b207ec163e394acb67d90bd3903be95dde69f57482f1087fb"},"schema_version":"1.0"},"canonical_sha256":"6c3560531c11758c67a1dea68b0d09c9e7f09b85004121dd120ef8b3877fdb4d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:36:49.965249Z","signature_b64":"r3/RC37+zF5hiCk9zv4sYsN0PM4tDSZyPyZpZo5vXRLaM9BYueSZtNZ9eXSWSNz1OV1K+u4wac8BJHw61KVzCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6c3560531c11758c67a1dea68b0d09c9e7f09b85004121dd120ef8b3877fdb4d","last_reissued_at":"2026-07-05T00:36:49.964839Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:36:49.964839Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2001.10122","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":"2026-07-05T00:36:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QJVIiiM8vgBkdC97gcb/LUxUZhtElDfdWJ9WkR5U72T5s5eGXZkGRk6mXEVhi652TsqEugv1jjqqriysAwFKDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T19:09:05.785458Z"},"content_sha256":"d00bc8f140c28b2661056c9db41ebcae9b576da714b868a0730f7e6b36f2f3b2","schema_version":"1.0","event_id":"sha256:d00bc8f140c28b2661056c9db41ebcae9b576da714b868a0730f7e6b36f2f3b2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:NQ2WAUY4CF2YYZ5B32TIWDIJZH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Regret Bounds for Decentralized Learning in Cooperative Multi-Agent Dynamical Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MA","math.OC","stat.ML"],"primary_cat":"cs.LG","authors_text":"Ashutosh Nayyar, Seyed Mohammad Asghari, Yi Ouyang","submitted_at":"2020-01-27T23:37:41Z","abstract_excerpt":"Regret analysis is challenging in Multi-Agent Reinforcement Learning (MARL) primarily due to the dynamical environments and the decentralized information among agents. We attempt to solve this challenge in the context of decentralized learning in multi-agent linear-quadratic (LQ) dynamical systems. We begin with a simple setup consisting of two agents and two dynamically decoupled stochastic linear systems, each system controlled by an agent. The systems are coupled through a quadratic cost function. When both systems' dynamics are unknown and there is no communication among the agents, we sho"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.10122","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/2001.10122/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":"2026-07-05T00:36:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C7nK4Nc456gH29D0Nsx6BSJXKShtrqCcdjhQRGaIhVc+f6r9z6ApvPdT0bRiekt7erDBW5ZC/PRNTeRPmUqyAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T19:09:05.785981Z"},"content_sha256":"92c334e80994319f179fbe9c567ed180a61abfda6cd7158dab2bb0cbcc508d7c","schema_version":"1.0","event_id":"sha256:92c334e80994319f179fbe9c567ed180a61abfda6cd7158dab2bb0cbcc508d7c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NQ2WAUY4CF2YYZ5B32TIWDIJZH/bundle.json","state_url":"https://pith.science/pith/NQ2WAUY4CF2YYZ5B32TIWDIJZH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NQ2WAUY4CF2YYZ5B32TIWDIJZH/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":"2026-08-23T19:09:05Z","links":{"resolver":"https://pith.science/pith/NQ2WAUY4CF2YYZ5B32TIWDIJZH","bundle":"https://pith.science/pith/NQ2WAUY4CF2YYZ5B32TIWDIJZH/bundle.json","state":"https://pith.science/pith/NQ2WAUY4CF2YYZ5B32TIWDIJZH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NQ2WAUY4CF2YYZ5B32TIWDIJZH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:NQ2WAUY4CF2YYZ5B32TIWDIJZH","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":"4f11fee009b16e9b207ec163e394acb67d90bd3903be95dde69f57482f1087fb","cross_cats_sorted":["cs.MA","math.OC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-27T23:37:41Z","title_canon_sha256":"419827408279cb59e4c8dd0fdd5a9c44f045d1e1bf8fe8ce26e162b20391932d"},"schema_version":"1.0","source":{"id":"2001.10122","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.10122","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"arxiv_version","alias_value":"2001.10122v1","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.10122","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"pith_short_12","alias_value":"NQ2WAUY4CF2Y","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"pith_short_16","alias_value":"NQ2WAUY4CF2YYZ5B","created_at":"2026-07-05T00:36:49Z"},{"alias_kind":"pith_short_8","alias_value":"NQ2WAUY4","created_at":"2026-07-05T00:36:49Z"}],"graph_snapshots":[{"event_id":"sha256:92c334e80994319f179fbe9c567ed180a61abfda6cd7158dab2bb0cbcc508d7c","target":"graph","created_at":"2026-07-05T00:36:49Z","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/2001.10122/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Regret analysis is challenging in Multi-Agent Reinforcement Learning (MARL) primarily due to the dynamical environments and the decentralized information among agents. We attempt to solve this challenge in the context of decentralized learning in multi-agent linear-quadratic (LQ) dynamical systems. We begin with a simple setup consisting of two agents and two dynamically decoupled stochastic linear systems, each system controlled by an agent. The systems are coupled through a quadratic cost function. When both systems' dynamics are unknown and there is no communication among the agents, we sho","authors_text":"Ashutosh Nayyar, Seyed Mohammad Asghari, Yi Ouyang","cross_cats":["cs.MA","math.OC","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-27T23:37:41Z","title":"Regret Bounds for Decentralized Learning in Cooperative Multi-Agent Dynamical Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.10122","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:d00bc8f140c28b2661056c9db41ebcae9b576da714b868a0730f7e6b36f2f3b2","target":"record","created_at":"2026-07-05T00:36:49Z","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":"4f11fee009b16e9b207ec163e394acb67d90bd3903be95dde69f57482f1087fb","cross_cats_sorted":["cs.MA","math.OC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-01-27T23:37:41Z","title_canon_sha256":"419827408279cb59e4c8dd0fdd5a9c44f045d1e1bf8fe8ce26e162b20391932d"},"schema_version":"1.0","source":{"id":"2001.10122","kind":"arxiv","version":1}},"canonical_sha256":"6c3560531c11758c67a1dea68b0d09c9e7f09b85004121dd120ef8b3877fdb4d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6c3560531c11758c67a1dea68b0d09c9e7f09b85004121dd120ef8b3877fdb4d","first_computed_at":"2026-07-05T00:36:49.964839Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:36:49.964839Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r3/RC37+zF5hiCk9zv4sYsN0PM4tDSZyPyZpZo5vXRLaM9BYueSZtNZ9eXSWSNz1OV1K+u4wac8BJHw61KVzCg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:36:49.965249Z","signed_message":"canonical_sha256_bytes"},"source_id":"2001.10122","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d00bc8f140c28b2661056c9db41ebcae9b576da714b868a0730f7e6b36f2f3b2","sha256:92c334e80994319f179fbe9c567ed180a61abfda6cd7158dab2bb0cbcc508d7c"],"state_sha256":"d009168067936a63361c10ed0b1617571596a5a2f8260f2bbbb57964f0123ef6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KPa64ocPPK0SX5Bav7l765dkafE1vv88xrQIOLrk2zLCRmyHn0Vgh+92f17d+ZP+JTGetnGMm2cOqSJxoHcJDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T19:09:05.790039Z","bundle_sha256":"cba696cb88ce40f8eea38e689e73be28fc5b226acbaa86109500eb815ebb5181"}}