{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GRCFLRHCC62RYYAXYCBURUBYZ7","short_pith_number":"pith:GRCFLRHC","canonical_record":{"source":{"id":"2412.14218","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T13:50:31Z","cross_cats_sorted":["cs.AI","cs.NI"],"title_canon_sha256":"da71269e0135798cc79eb61fb142421271afd50c970b477f8865c578ea10a457","abstract_canon_sha256":"d9f8c875dcb503abc543c669b70ea552312f29abe3bf4dd447c0f6ff9e80e2c9"},"schema_version":"1.0"},"canonical_sha256":"344455c4e217b51c6017c08348d038cff4c8f16b872337dfa49a9c61bd906860","source":{"kind":"arxiv","id":"2412.14218","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.14218","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"arxiv_version","alias_value":"2412.14218v2","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.14218","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"pith_short_12","alias_value":"GRCFLRHCC62R","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"pith_short_16","alias_value":"GRCFLRHCC62RYYAX","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"pith_short_8","alias_value":"GRCFLRHC","created_at":"2026-07-05T11:20:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GRCFLRHCC62RYYAXYCBURUBYZ7","target":"record","payload":{"canonical_record":{"source":{"id":"2412.14218","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T13:50:31Z","cross_cats_sorted":["cs.AI","cs.NI"],"title_canon_sha256":"da71269e0135798cc79eb61fb142421271afd50c970b477f8865c578ea10a457","abstract_canon_sha256":"d9f8c875dcb503abc543c669b70ea552312f29abe3bf4dd447c0f6ff9e80e2c9"},"schema_version":"1.0"},"canonical_sha256":"344455c4e217b51c6017c08348d038cff4c8f16b872337dfa49a9c61bd906860","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:20:07.148450Z","signature_b64":"Hb2AUi3BT1sG8QOgkRgaew0lnqpj+iLnenqWnV0nyAFOynBAIALUnpqPzqLWN68i+BU8d53VgeQ4HjUAHmvGDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"344455c4e217b51c6017c08348d038cff4c8f16b872337dfa49a9c61bd906860","last_reissued_at":"2026-07-05T11:20:07.147906Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:20:07.147906Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.14218","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:20:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/DufdUtRKZ6DUC+eK8n+L15cSdMBOK5uxRyYGUwUJtHiwGQxA4dJUtR1yeYBmDeAUh8MJk4ukEAdYMooX7xPAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:48:07.709852Z"},"content_sha256":"55d848f79aa7541efb0c4ae9f69565757d7740828b20fc3c0d4604cef23619be","schema_version":"1.0","event_id":"sha256:55d848f79aa7541efb0c4ae9f69565757d7740828b20fc3c0d4604cef23619be"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GRCFLRHCC62RYYAXYCBURUBYZ7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Heterogeneous Multi-Agent Reinforcement Learning for Distributed Channel Access in WLANs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.NI"],"primary_cat":"cs.LG","authors_text":"Chongtao Guo, Geoffrey Ye Li, Jiaming Yu, Le Liang, Shi Jin, Ziyang Guo","submitted_at":"2024-12-18T13:50:31Z","abstract_excerpt":"This paper investigates the use of multi-agent reinforcement learning (MARL) to address distributed channel access in wireless local area networks. In particular, we consider the challenging yet more practical case where the agents heterogeneously adopt value-based or policy-based reinforcement learning algorithms to train the model. We propose a heterogeneous MARL training framework, named QPMIX, which adopts a centralized training with distributed execution paradigm to enable heterogeneous agents to collaborate. Moreover, we theoretically prove the convergence of the proposed heterogeneous M"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.14218","kind":"arxiv","version":2},"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/2412.14218/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":"2026-07-05T11:20:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zimjith6O5yBGyAghrfQvjr+Beoh1F472EsbR9WamsXZo9vbZl6lgpQFntFSrfoDcRr+COxORAq4FaShsV06Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:48:07.710231Z"},"content_sha256":"52d018a7f72756274067f5ec5d02c7ff021b0a5e052bff4bd255eea10aa80c48","schema_version":"1.0","event_id":"sha256:52d018a7f72756274067f5ec5d02c7ff021b0a5e052bff4bd255eea10aa80c48"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GRCFLRHCC62RYYAXYCBURUBYZ7/bundle.json","state_url":"https://pith.science/pith/GRCFLRHCC62RYYAXYCBURUBYZ7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GRCFLRHCC62RYYAXYCBURUBYZ7/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":"2026-07-06T17:48:07Z","links":{"resolver":"https://pith.science/pith/GRCFLRHCC62RYYAXYCBURUBYZ7","bundle":"https://pith.science/pith/GRCFLRHCC62RYYAXYCBURUBYZ7/bundle.json","state":"https://pith.science/pith/GRCFLRHCC62RYYAXYCBURUBYZ7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GRCFLRHCC62RYYAXYCBURUBYZ7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GRCFLRHCC62RYYAXYCBURUBYZ7","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":"d9f8c875dcb503abc543c669b70ea552312f29abe3bf4dd447c0f6ff9e80e2c9","cross_cats_sorted":["cs.AI","cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T13:50:31Z","title_canon_sha256":"da71269e0135798cc79eb61fb142421271afd50c970b477f8865c578ea10a457"},"schema_version":"1.0","source":{"id":"2412.14218","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.14218","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"arxiv_version","alias_value":"2412.14218v2","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.14218","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"pith_short_12","alias_value":"GRCFLRHCC62R","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"pith_short_16","alias_value":"GRCFLRHCC62RYYAX","created_at":"2026-07-05T11:20:07Z"},{"alias_kind":"pith_short_8","alias_value":"GRCFLRHC","created_at":"2026-07-05T11:20:07Z"}],"graph_snapshots":[{"event_id":"sha256:52d018a7f72756274067f5ec5d02c7ff021b0a5e052bff4bd255eea10aa80c48","target":"graph","created_at":"2026-07-05T11:20:07Z","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/2412.14218/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper investigates the use of multi-agent reinforcement learning (MARL) to address distributed channel access in wireless local area networks. In particular, we consider the challenging yet more practical case where the agents heterogeneously adopt value-based or policy-based reinforcement learning algorithms to train the model. We propose a heterogeneous MARL training framework, named QPMIX, which adopts a centralized training with distributed execution paradigm to enable heterogeneous agents to collaborate. Moreover, we theoretically prove the convergence of the proposed heterogeneous M","authors_text":"Chongtao Guo, Geoffrey Ye Li, Jiaming Yu, Le Liang, Shi Jin, Ziyang Guo","cross_cats":["cs.AI","cs.NI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T13:50:31Z","title":"Heterogeneous Multi-Agent Reinforcement Learning for Distributed Channel Access in WLANs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.14218","kind":"arxiv","version":2},"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":"sha256:55d848f79aa7541efb0c4ae9f69565757d7740828b20fc3c0d4604cef23619be","target":"record","created_at":"2026-07-05T11:20:07Z","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":"d9f8c875dcb503abc543c669b70ea552312f29abe3bf4dd447c0f6ff9e80e2c9","cross_cats_sorted":["cs.AI","cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-18T13:50:31Z","title_canon_sha256":"da71269e0135798cc79eb61fb142421271afd50c970b477f8865c578ea10a457"},"schema_version":"1.0","source":{"id":"2412.14218","kind":"arxiv","version":2}},"canonical_sha256":"344455c4e217b51c6017c08348d038cff4c8f16b872337dfa49a9c61bd906860","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"344455c4e217b51c6017c08348d038cff4c8f16b872337dfa49a9c61bd906860","first_computed_at":"2026-07-05T11:20:07.147906Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:20:07.147906Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Hb2AUi3BT1sG8QOgkRgaew0lnqpj+iLnenqWnV0nyAFOynBAIALUnpqPzqLWN68i+BU8d53VgeQ4HjUAHmvGDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:20:07.148450Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.14218","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:55d848f79aa7541efb0c4ae9f69565757d7740828b20fc3c0d4604cef23619be","sha256:52d018a7f72756274067f5ec5d02c7ff021b0a5e052bff4bd255eea10aa80c48"],"state_sha256":"ab30a1ea7fc8bcbd1dd3394f597aec88ef4b72be460dbccab7929b06a26b9611"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bfCnnaDjw/9uF6jpqIW7PqXYFd+xZXGP3/rxDL3QxjyuabhnpDRr8YOvR0v9kHb/GCKXQnZcrE3l3PwhsZw8Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T17:48:07.712248Z","bundle_sha256":"3724e1034e8d74870eba539a855035ee242ed4d9b77f4d7d39158747707501cb"}}