{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:MPWU3WJ4LUMILHFDALZZDEA4ZO","short_pith_number":"pith:MPWU3WJ4","canonical_record":{"source":{"id":"2404.08003","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T04:21:13Z","cross_cats_sorted":["cs.DC","cs.NI"],"title_canon_sha256":"91e9d0448fc0ee066f906864984790cae657788da20c931cf8650dbf2d2a6531","abstract_canon_sha256":"1c7ada37838543a3e5dfcb66771a257a740c09af0a13866662b9083d5ed4c0af"},"schema_version":"1.0"},"canonical_sha256":"63ed4dd93c5d18859ca302f391901ccb90ae71316151ced117703f4b013f43dc","source":{"kind":"arxiv","id":"2404.08003","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.08003","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"arxiv_version","alias_value":"2404.08003v5","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.08003","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"pith_short_12","alias_value":"MPWU3WJ4LUMI","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"pith_short_16","alias_value":"MPWU3WJ4LUMILHFD","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"pith_short_8","alias_value":"MPWU3WJ4","created_at":"2026-07-05T10:04:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:MPWU3WJ4LUMILHFDALZZDEA4ZO","target":"record","payload":{"canonical_record":{"source":{"id":"2404.08003","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T04:21:13Z","cross_cats_sorted":["cs.DC","cs.NI"],"title_canon_sha256":"91e9d0448fc0ee066f906864984790cae657788da20c931cf8650dbf2d2a6531","abstract_canon_sha256":"1c7ada37838543a3e5dfcb66771a257a740c09af0a13866662b9083d5ed4c0af"},"schema_version":"1.0"},"canonical_sha256":"63ed4dd93c5d18859ca302f391901ccb90ae71316151ced117703f4b013f43dc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:04:38.289366Z","signature_b64":"aBQtS3ywMKfNI2b5eAPJe/77xmJiG27ahATiJjf2aqrrDDFzVUp7cPY5KKK5PQSgbob2CfXlQ2orYKxS5AJnDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"63ed4dd93c5d18859ca302f391901ccb90ae71316151ced117703f4b013f43dc","last_reissued_at":"2026-07-05T10:04:38.288816Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:04:38.288816Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.08003","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:04:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZiAw1dUn4/k1Ykk1jua7sU5mIuBroJaBFa/LdNzeVtSm1NSK5TI3hfF1BYTs8lWEUw+lQRS1qXjws3wuWeerCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T11:17:33.662121Z"},"content_sha256":"5d4bb1425689b02636160e7e17bfce2e13086da0873e6bf6e013a1129c8afe3f","schema_version":"1.0","event_id":"sha256:5d4bb1425689b02636160e7e17bfce2e13086da0873e6bf6e013a1129c8afe3f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:MPWU3WJ4LUMILHFDALZZDEA4ZO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DC","cs.NI"],"primary_cat":"cs.LG","authors_text":"Abolfazl Hashemi, Christopher G. Brinton, Dong-Jun Han, Guangchen Lan, Vaneet Aggarwal","submitted_at":"2024-04-09T04:21:13Z","abstract_excerpt":"To improve the efficiency of reinforcement learning (RL), we propose a novel asynchronous federated reinforcement learning (FedRL) framework termed AFedPG, which constructs a global model through collaboration among $N$ agents using policy gradient (PG) updates. To address the challenge of lagged policies in asynchronous settings, we design a delay-adaptive lookahead technique \\textit{specifically for FedRL} that can effectively handle heterogeneous arrival times of policy gradients. We analyze the theoretical global convergence bound of AFedPG, and characterize the advantage of the proposed a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.08003","kind":"arxiv","version":5},"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/2404.08003/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":"2026-07-05T10:04:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b19jEEaVzJdrwivpxxMcPw8jy9YxJ8vdM0XxtC158sz25ZSrTc+64hmktUQ6i6y7IJ924hMLmnZvbGcA4UkUAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T11:17:33.662631Z"},"content_sha256":"2a52927e4d0e2bb0ec1c8d05f9c271ecedcf3ed5c45fa1681c4ca4c82b374994","schema_version":"1.0","event_id":"sha256:2a52927e4d0e2bb0ec1c8d05f9c271ecedcf3ed5c45fa1681c4ca4c82b374994"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MPWU3WJ4LUMILHFDALZZDEA4ZO/bundle.json","state_url":"https://pith.science/pith/MPWU3WJ4LUMILHFDALZZDEA4ZO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MPWU3WJ4LUMILHFDALZZDEA4ZO/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":"2026-08-07T11:17:33Z","links":{"resolver":"https://pith.science/pith/MPWU3WJ4LUMILHFDALZZDEA4ZO","bundle":"https://pith.science/pith/MPWU3WJ4LUMILHFDALZZDEA4ZO/bundle.json","state":"https://pith.science/pith/MPWU3WJ4LUMILHFDALZZDEA4ZO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MPWU3WJ4LUMILHFDALZZDEA4ZO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MPWU3WJ4LUMILHFDALZZDEA4ZO","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":"1c7ada37838543a3e5dfcb66771a257a740c09af0a13866662b9083d5ed4c0af","cross_cats_sorted":["cs.DC","cs.NI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T04:21:13Z","title_canon_sha256":"91e9d0448fc0ee066f906864984790cae657788da20c931cf8650dbf2d2a6531"},"schema_version":"1.0","source":{"id":"2404.08003","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.08003","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"arxiv_version","alias_value":"2404.08003v5","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.08003","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"pith_short_12","alias_value":"MPWU3WJ4LUMI","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"pith_short_16","alias_value":"MPWU3WJ4LUMILHFD","created_at":"2026-07-05T10:04:38Z"},{"alias_kind":"pith_short_8","alias_value":"MPWU3WJ4","created_at":"2026-07-05T10:04:38Z"}],"graph_snapshots":[{"event_id":"sha256:2a52927e4d0e2bb0ec1c8d05f9c271ecedcf3ed5c45fa1681c4ca4c82b374994","target":"graph","created_at":"2026-07-05T10:04:38Z","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/2404.08003/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"To improve the efficiency of reinforcement learning (RL), we propose a novel asynchronous federated reinforcement learning (FedRL) framework termed AFedPG, which constructs a global model through collaboration among $N$ agents using policy gradient (PG) updates. To address the challenge of lagged policies in asynchronous settings, we design a delay-adaptive lookahead technique \\textit{specifically for FedRL} that can effectively handle heterogeneous arrival times of policy gradients. We analyze the theoretical global convergence bound of AFedPG, and characterize the advantage of the proposed a","authors_text":"Abolfazl Hashemi, Christopher G. Brinton, Dong-Jun Han, Guangchen Lan, Vaneet Aggarwal","cross_cats":["cs.DC","cs.NI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T04:21:13Z","title":"Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.08003","kind":"arxiv","version":5},"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":"sha256:5d4bb1425689b02636160e7e17bfce2e13086da0873e6bf6e013a1129c8afe3f","target":"record","created_at":"2026-07-05T10:04:38Z","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":"1c7ada37838543a3e5dfcb66771a257a740c09af0a13866662b9083d5ed4c0af","cross_cats_sorted":["cs.DC","cs.NI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-09T04:21:13Z","title_canon_sha256":"91e9d0448fc0ee066f906864984790cae657788da20c931cf8650dbf2d2a6531"},"schema_version":"1.0","source":{"id":"2404.08003","kind":"arxiv","version":5}},"canonical_sha256":"63ed4dd93c5d18859ca302f391901ccb90ae71316151ced117703f4b013f43dc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"63ed4dd93c5d18859ca302f391901ccb90ae71316151ced117703f4b013f43dc","first_computed_at":"2026-07-05T10:04:38.288816Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:04:38.288816Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aBQtS3ywMKfNI2b5eAPJe/77xmJiG27ahATiJjf2aqrrDDFzVUp7cPY5KKK5PQSgbob2CfXlQ2orYKxS5AJnDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:04:38.289366Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.08003","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5d4bb1425689b02636160e7e17bfce2e13086da0873e6bf6e013a1129c8afe3f","sha256:2a52927e4d0e2bb0ec1c8d05f9c271ecedcf3ed5c45fa1681c4ca4c82b374994"],"state_sha256":"3e8b57460cf2cee579f4e78295e388379d87339e76e24fa5ccebbcc90633dfa5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sufbGJkTSE0kv0H+YNIngBTst8+mg+UfdXDYvITcAMWzaEuTUGSveMdf6KHWW1sKebP3/2WS+1dFtxls7yaXAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T11:17:33.668703Z","bundle_sha256":"42cb398dae162b25cf26e5bf3e1bcc25cd100bbcd1d1e83c15b35f475b03762b"}}