{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:AQJJ4J3IUCBUINJPIAXSV3FTZS","short_pith_number":"pith:AQJJ4J3I","schema_version":"1.0","canonical_sha256":"04129e2768a08344352f402f2aecb3cca07a22980a7f1f98977b3a12ab8c4587","source":{"kind":"arxiv","id":"2206.06758","version":3},"attestation_state":"computed","paper":{"title":"Universally Expressive Communication in Multi-Agent Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DM","cs.LG"],"primary_cat":"cs.MA","authors_text":"Arnu Pretorius, Matthew Morris, Thomas D. Barrett","submitted_at":"2022-06-14T11:16:33Z","abstract_excerpt":"Allowing agents to share information through communication is crucial for solving complex tasks in multi-agent reinforcement learning. In this work, we consider the question of whether a given communication protocol can express an arbitrary policy. By observing that many existing protocols can be viewed as instances of graph neural networks (GNNs), we demonstrate the equivalence of joint action selection to node labelling. With standard GNN approaches provably limited in their expressive capacity, we draw from existing GNN literature and consider augmenting agent observations with: (1) unique "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2206.06758","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MA","submitted_at":"2022-06-14T11:16:33Z","cross_cats_sorted":["cs.DM","cs.LG"],"title_canon_sha256":"3b42ee87ac0563762287eb777ba5cca500f34224a5b972a07004dacf4cb38730","abstract_canon_sha256":"a8d9f13783c0c76bd3cd8177597c397454ae99d75929256cb79982897a10dc3b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:32:45.053871Z","signature_b64":"SwLYFV8kN36FL+oxvYCEN2y+tWhngADZsE+8pVAyza+ogbSU36ymG833vFVzDLhDCVGZ729VCWnxg3MYFVAbBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"04129e2768a08344352f402f2aecb3cca07a22980a7f1f98977b3a12ab8c4587","last_reissued_at":"2026-07-05T05:32:45.053333Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:32:45.053333Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Universally Expressive Communication in Multi-Agent Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DM","cs.LG"],"primary_cat":"cs.MA","authors_text":"Arnu Pretorius, Matthew Morris, Thomas D. Barrett","submitted_at":"2022-06-14T11:16:33Z","abstract_excerpt":"Allowing agents to share information through communication is crucial for solving complex tasks in multi-agent reinforcement learning. In this work, we consider the question of whether a given communication protocol can express an arbitrary policy. By observing that many existing protocols can be viewed as instances of graph neural networks (GNNs), we demonstrate the equivalence of joint action selection to node labelling. With standard GNN approaches provably limited in their expressive capacity, we draw from existing GNN literature and consider augmenting agent observations with: (1) unique "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.06758","kind":"arxiv","version":3},"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/2206.06758/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2206.06758","created_at":"2026-07-05T05:32:45.053392+00:00"},{"alias_kind":"arxiv_version","alias_value":"2206.06758v3","created_at":"2026-07-05T05:32:45.053392+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.06758","created_at":"2026-07-05T05:32:45.053392+00:00"},{"alias_kind":"pith_short_12","alias_value":"AQJJ4J3IUCBU","created_at":"2026-07-05T05:32:45.053392+00:00"},{"alias_kind":"pith_short_16","alias_value":"AQJJ4J3IUCBUINJP","created_at":"2026-07-05T05:32:45.053392+00:00"},{"alias_kind":"pith_short_8","alias_value":"AQJJ4J3I","created_at":"2026-07-05T05:32:45.053392+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AQJJ4J3IUCBUINJPIAXSV3FTZS","json":"https://pith.science/pith/AQJJ4J3IUCBUINJPIAXSV3FTZS.json","graph_json":"https://pith.science/api/pith-number/AQJJ4J3IUCBUINJPIAXSV3FTZS/graph.json","events_json":"https://pith.science/api/pith-number/AQJJ4J3IUCBUINJPIAXSV3FTZS/events.json","paper":"https://pith.science/paper/AQJJ4J3I"},"agent_actions":{"view_html":"https://pith.science/pith/AQJJ4J3IUCBUINJPIAXSV3FTZS","download_json":"https://pith.science/pith/AQJJ4J3IUCBUINJPIAXSV3FTZS.json","view_paper":"https://pith.science/paper/AQJJ4J3I","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2206.06758&json=true","fetch_graph":"https://pith.science/api/pith-number/AQJJ4J3IUCBUINJPIAXSV3FTZS/graph.json","fetch_events":"https://pith.science/api/pith-number/AQJJ4J3IUCBUINJPIAXSV3FTZS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AQJJ4J3IUCBUINJPIAXSV3FTZS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AQJJ4J3IUCBUINJPIAXSV3FTZS/action/storage_attestation","attest_author":"https://pith.science/pith/AQJJ4J3IUCBUINJPIAXSV3FTZS/action/author_attestation","sign_citation":"https://pith.science/pith/AQJJ4J3IUCBUINJPIAXSV3FTZS/action/citation_signature","submit_replication":"https://pith.science/pith/AQJJ4J3IUCBUINJPIAXSV3FTZS/action/replication_record"}},"created_at":"2026-07-05T05:32:45.053392+00:00","updated_at":"2026-07-05T05:32:45.053392+00:00"}