{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:OPDCFWG5BNC5OVJ5OFB2S2QXBC","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":"059b8fff4649f6f4f5c368c182a3809e53dd11d212472e845ccb8bdb275135d5","cross_cats_sorted":["cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-09-30T14:46:18Z","title_canon_sha256":"8764fa265d21ed212898885d130a0e5b53277d2a57204362376c4e62395e31de"},"schema_version":"1.0","source":{"id":"2109.15175","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.15175","created_at":"2026-07-05T03:18:56Z"},{"alias_kind":"arxiv_version","alias_value":"2109.15175v1","created_at":"2026-07-05T03:18:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.15175","created_at":"2026-07-05T03:18:56Z"},{"alias_kind":"pith_short_12","alias_value":"OPDCFWG5BNC5","created_at":"2026-07-05T03:18:56Z"},{"alias_kind":"pith_short_16","alias_value":"OPDCFWG5BNC5OVJ5","created_at":"2026-07-05T03:18:56Z"},{"alias_kind":"pith_short_8","alias_value":"OPDCFWG5","created_at":"2026-07-05T03:18:56Z"}],"graph_snapshots":[{"event_id":"sha256:d28203163ac8dad73382b99095923560b382f3a9a8ba753de060d7a1f393655a","target":"graph","created_at":"2026-07-05T03:18:56Z","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/2109.15175/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mobile networks are composed of many base stations and for each of them many parameters must be optimized to provide good services. Automatically and dynamically optimizing all these entities is challenging as they are sensitive to variations in the environment and can affect each other through interferences. Reinforcement learning (RL) algorithms are good candidates to automatically learn base station configuration strategies from incoming data but they are often hard to scale to many agents. In this work, we demonstrate how to use coordination graphs and reinforcement learning in a complex a","authors_text":"Hasan Farooq, Julien Forgeat, Maxime Bouton, Meral Shirazipour, Per Karlsson, Shruti Bothe","cross_cats":["cs.NI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-09-30T14:46:18Z","title":"Coordinated Reinforcement Learning for Optimizing Mobile Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.15175","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:e85b8ccfcec7d425a0d134f93cbb0bf50e7699d2cee1a6d4104827c8799ef889","target":"record","created_at":"2026-07-05T03:18:56Z","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":"059b8fff4649f6f4f5c368c182a3809e53dd11d212472e845ccb8bdb275135d5","cross_cats_sorted":["cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-09-30T14:46:18Z","title_canon_sha256":"8764fa265d21ed212898885d130a0e5b53277d2a57204362376c4e62395e31de"},"schema_version":"1.0","source":{"id":"2109.15175","kind":"arxiv","version":1}},"canonical_sha256":"73c622d8dd0b45d7553d7143a96a1708ae78ccd4a456e7f513fa1fc175a43011","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"73c622d8dd0b45d7553d7143a96a1708ae78ccd4a456e7f513fa1fc175a43011","first_computed_at":"2026-07-05T03:18:56.302038Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:18:56.302038Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"x8OLr8I3imZU7H1nH+q6ahQWLKAlF6VH7kDQOmwAXoVoHXqEhcZ579XSBMI3YPz5kSxT/gHGO40So5JFEKLJBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:18:56.302455Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.15175","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e85b8ccfcec7d425a0d134f93cbb0bf50e7699d2cee1a6d4104827c8799ef889","sha256:d28203163ac8dad73382b99095923560b382f3a9a8ba753de060d7a1f393655a"],"state_sha256":"84eb1050e81fb3c7037e3db7042f27bf218ae929124aa13079033875fbd8343b"}