{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:37SV7DLOW2UHYCY3RPXJ26I4R3","short_pith_number":"pith:37SV7DLO","canonical_record":{"source":{"id":"2203.08454","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-16T08:22:45Z","cross_cats_sorted":["cs.MA"],"title_canon_sha256":"48a1749cf94c2fc9bec43427c7c8ad2877e8f0f34c84d1e7d17f70e0fa671555","abstract_canon_sha256":"416ca9294c6ef6ef599c00f224b0405fae109b0dc8d1346bbaf5e75dff8ae428"},"schema_version":"1.0"},"canonical_sha256":"dfe55f8d6eb6a87c0b1b8bee9d791c8ec90b08bd3d6bbe7d2fabdbb153c4cbe8","source":{"kind":"arxiv","id":"2203.08454","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.08454","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"arxiv_version","alias_value":"2203.08454v1","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.08454","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"pith_short_12","alias_value":"37SV7DLOW2UH","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"pith_short_16","alias_value":"37SV7DLOW2UHYCY3","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"pith_short_8","alias_value":"37SV7DLO","created_at":"2026-07-05T04:05:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:37SV7DLOW2UHYCY3RPXJ26I4R3","target":"record","payload":{"canonical_record":{"source":{"id":"2203.08454","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-16T08:22:45Z","cross_cats_sorted":["cs.MA"],"title_canon_sha256":"48a1749cf94c2fc9bec43427c7c8ad2877e8f0f34c84d1e7d17f70e0fa671555","abstract_canon_sha256":"416ca9294c6ef6ef599c00f224b0405fae109b0dc8d1346bbaf5e75dff8ae428"},"schema_version":"1.0"},"canonical_sha256":"dfe55f8d6eb6a87c0b1b8bee9d791c8ec90b08bd3d6bbe7d2fabdbb153c4cbe8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:05:44.816478Z","signature_b64":"xwKZvEIoLx0MBNDCYc9ig66aAvbL+dUGW6Tt+SReBVAWrWZJ6Rcf3G6WSg71Mt/LvSW19YA5L3LSchv8ZXoUBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dfe55f8d6eb6a87c0b1b8bee9d791c8ec90b08bd3d6bbe7d2fabdbb153c4cbe8","last_reissued_at":"2026-07-05T04:05:44.816013Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:05:44.816013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.08454","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":"2026-07-05T04:05:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I3R5thElW587VuB/mOqRv5Tvkdt+VvhSr2wDJ5bv+q/WrZrlFGf7IFYdzMF6IWjMXU9MpE6FMX6d7PeCNVuACw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T17:45:44.357267Z"},"content_sha256":"94ebfeaacdbce78c68e74b72a1419516a9f2adb416fc38dde53f10f04a306bca","schema_version":"1.0","event_id":"sha256:94ebfeaacdbce78c68e74b72a1419516a9f2adb416fc38dde53f10f04a306bca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:37SV7DLOW2UHYCY3RPXJ26I4R3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"cs.LG","authors_text":"Houqiang Li, Jianye Hao, Jian Zhao, Mingyu Yang, Weixun Wang, Wengang Zhou, Xunhan Hu, Youpeng Zhao","submitted_at":"2022-03-16T08:22:45Z","abstract_excerpt":"Multi-agent reinforcement learning is difficult to be applied in practice, which is partially due to the gap between the simulated and real-world scenarios. One reason for the gap is that the simulated systems always assume that the agents can work normally all the time, while in practice, one or more agents may unexpectedly \"crash\" during the coordination process due to inevitable hardware or software failures. Such crashes will destroy the cooperation among agents, leading to performance degradation. In this work, we present a formal formulation of a cooperative multi-agent reinforcement lea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.08454","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/2203.08454/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":"2026-07-05T04:05:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ju+2nPTwhMN26ymq4r4xIzQ3/3WvNFkkjPXEzwMhp8A1qg6ZQI7qVL6O0pzU6LkksfGT619VHXTRjmnTSF4eAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T17:45:44.357650Z"},"content_sha256":"3c99fd3535ce5ab7fccf63dd7d352b9dc32628cdeee6f8fa36de2e22b5e7fc9e","schema_version":"1.0","event_id":"sha256:3c99fd3535ce5ab7fccf63dd7d352b9dc32628cdeee6f8fa36de2e22b5e7fc9e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/37SV7DLOW2UHYCY3RPXJ26I4R3/bundle.json","state_url":"https://pith.science/pith/37SV7DLOW2UHYCY3RPXJ26I4R3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/37SV7DLOW2UHYCY3RPXJ26I4R3/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":"2026-08-06T17:45:44Z","links":{"resolver":"https://pith.science/pith/37SV7DLOW2UHYCY3RPXJ26I4R3","bundle":"https://pith.science/pith/37SV7DLOW2UHYCY3RPXJ26I4R3/bundle.json","state":"https://pith.science/pith/37SV7DLOW2UHYCY3RPXJ26I4R3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/37SV7DLOW2UHYCY3RPXJ26I4R3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:37SV7DLOW2UHYCY3RPXJ26I4R3","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":"416ca9294c6ef6ef599c00f224b0405fae109b0dc8d1346bbaf5e75dff8ae428","cross_cats_sorted":["cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-16T08:22:45Z","title_canon_sha256":"48a1749cf94c2fc9bec43427c7c8ad2877e8f0f34c84d1e7d17f70e0fa671555"},"schema_version":"1.0","source":{"id":"2203.08454","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.08454","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"arxiv_version","alias_value":"2203.08454v1","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.08454","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"pith_short_12","alias_value":"37SV7DLOW2UH","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"pith_short_16","alias_value":"37SV7DLOW2UHYCY3","created_at":"2026-07-05T04:05:44Z"},{"alias_kind":"pith_short_8","alias_value":"37SV7DLO","created_at":"2026-07-05T04:05:44Z"}],"graph_snapshots":[{"event_id":"sha256:3c99fd3535ce5ab7fccf63dd7d352b9dc32628cdeee6f8fa36de2e22b5e7fc9e","target":"graph","created_at":"2026-07-05T04:05:44Z","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/2203.08454/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-agent reinforcement learning is difficult to be applied in practice, which is partially due to the gap between the simulated and real-world scenarios. One reason for the gap is that the simulated systems always assume that the agents can work normally all the time, while in practice, one or more agents may unexpectedly \"crash\" during the coordination process due to inevitable hardware or software failures. Such crashes will destroy the cooperation among agents, leading to performance degradation. In this work, we present a formal formulation of a cooperative multi-agent reinforcement lea","authors_text":"Houqiang Li, Jianye Hao, Jian Zhao, Mingyu Yang, Weixun Wang, Wengang Zhou, Xunhan Hu, Youpeng Zhao","cross_cats":["cs.MA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-16T08:22:45Z","title":"Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.08454","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":"sha256:94ebfeaacdbce78c68e74b72a1419516a9f2adb416fc38dde53f10f04a306bca","target":"record","created_at":"2026-07-05T04:05:44Z","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":"416ca9294c6ef6ef599c00f224b0405fae109b0dc8d1346bbaf5e75dff8ae428","cross_cats_sorted":["cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-16T08:22:45Z","title_canon_sha256":"48a1749cf94c2fc9bec43427c7c8ad2877e8f0f34c84d1e7d17f70e0fa671555"},"schema_version":"1.0","source":{"id":"2203.08454","kind":"arxiv","version":1}},"canonical_sha256":"dfe55f8d6eb6a87c0b1b8bee9d791c8ec90b08bd3d6bbe7d2fabdbb153c4cbe8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dfe55f8d6eb6a87c0b1b8bee9d791c8ec90b08bd3d6bbe7d2fabdbb153c4cbe8","first_computed_at":"2026-07-05T04:05:44.816013Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:05:44.816013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xwKZvEIoLx0MBNDCYc9ig66aAvbL+dUGW6Tt+SReBVAWrWZJ6Rcf3G6WSg71Mt/LvSW19YA5L3LSchv8ZXoUBA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:05:44.816478Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.08454","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:94ebfeaacdbce78c68e74b72a1419516a9f2adb416fc38dde53f10f04a306bca","sha256:3c99fd3535ce5ab7fccf63dd7d352b9dc32628cdeee6f8fa36de2e22b5e7fc9e"],"state_sha256":"53c994d5e8596ca5fd637013701eb67cbeaf84b9fdbbfec5f4096d87a2fca2bd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RnDQ5tXLAYGwm9Z0uSqxD8XCs57gGqbgdDyDy4NOE2NzSovsmck11pXpVG6Y3q1qLI5X+53a/n0GLC4CHb9mBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T17:45:44.360294Z","bundle_sha256":"1bf28a22ea3bb1a1cce00cce0b472619d70b4a08b8e09fdd9167865443d6af88"}}