{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HY75ZXF7MVEQ3BWQAGRVZMPNFG","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":"25550ff2bbfad59ece1192c61f75deddb27590750e5764729f360c1b130c48f1","cross_cats_sorted":["cs.MA"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2024-07-27T00:03:14Z","title_canon_sha256":"eaeaa3455639549a74aa6aed19e118aa49c988149b7c00603caed3e7ce4b756f"},"schema_version":"1.0","source":{"id":"2407.19128","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.19128","created_at":"2026-07-05T08:49:14Z"},{"alias_kind":"arxiv_version","alias_value":"2407.19128v1","created_at":"2026-07-05T08:49:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.19128","created_at":"2026-07-05T08:49:14Z"},{"alias_kind":"pith_short_12","alias_value":"HY75ZXF7MVEQ","created_at":"2026-07-05T08:49:14Z"},{"alias_kind":"pith_short_16","alias_value":"HY75ZXF7MVEQ3BWQ","created_at":"2026-07-05T08:49:14Z"},{"alias_kind":"pith_short_8","alias_value":"HY75ZXF7","created_at":"2026-07-05T08:49:14Z"}],"graph_snapshots":[{"event_id":"sha256:e73067c6604207137f50e205a43d60dc00ae58506ac1bc0221508d9ff638b316","target":"graph","created_at":"2026-07-05T08:49:14Z","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/2407.19128/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Cooperative multi-agent learning methods are essential in developing effective cooperation strategies in multi-agent domains. In robotics, these methods extend beyond multi-robot scenarios to single-robot systems, where they enable coordination among different robot modules (e.g., robot legs or joints). However, current methods often struggle to quickly adapt to unforeseen failures, such as a malfunctioning robot leg, especially after the algorithm has converged to a strategy. To overcome this, we introduce the Relational Q-Functionals (RQF) framework. RQF leverages a relational network, repre","authors_text":"Kshitij Jerath, Paul Robinette, Reza Azadeh, Yasin Findik","cross_cats":["cs.MA"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2024-07-27T00:03:14Z","title":"Relational Q-Functionals: Multi-Agent Learning to Recover from Unforeseen Robot Malfunctions in Continuous Action Domains"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.19128","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:ef297c398b7f1b1912c57392c1a22d335728cfdbb8f4bdbc4bb9aadeb64ce503","target":"record","created_at":"2026-07-05T08:49:14Z","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":"25550ff2bbfad59ece1192c61f75deddb27590750e5764729f360c1b130c48f1","cross_cats_sorted":["cs.MA"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2024-07-27T00:03:14Z","title_canon_sha256":"eaeaa3455639549a74aa6aed19e118aa49c988149b7c00603caed3e7ce4b756f"},"schema_version":"1.0","source":{"id":"2407.19128","kind":"arxiv","version":1}},"canonical_sha256":"3e3fdcdcbf65490d86d001a35cb1ed29845d79a583d1f7996f816d5c1e873854","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e3fdcdcbf65490d86d001a35cb1ed29845d79a583d1f7996f816d5c1e873854","first_computed_at":"2026-07-05T08:49:14.629805Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:49:14.629805Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+LVwrfW9xnawnMOR5VY8oEiNlvCFBVFqBfRvzV8I6Pm+l6sNMMDBlMM6Rff8lARE2FokmZN7fYayWEMFgvmNDw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:49:14.630243Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.19128","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ef297c398b7f1b1912c57392c1a22d335728cfdbb8f4bdbc4bb9aadeb64ce503","sha256:e73067c6604207137f50e205a43d60dc00ae58506ac1bc0221508d9ff638b316"],"state_sha256":"cc27166ddb5ef0dda63cd418ee362ed635c742f8c063b3c38e2c2c31e759c59f"}