{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:P6QXBXDPQXYZNYAEIKM55HRIKI","short_pith_number":"pith:P6QXBXDP","schema_version":"1.0","canonical_sha256":"7fa170dc6f85f196e0044299de9e285218d3573df9c5ee772e6138055edacc1f","source":{"kind":"arxiv","id":"2511.02398","version":2},"attestation_state":"computed","paper":{"title":"A Spatially Informed Gaussian Process UCB Method for Decentralized Coverage Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Elia Raimondi, Florian D\\\"orfler, Gennaro Guidone, Han Wang, Luca Monegaglia, Mattia Bianchi","submitted_at":"2025-11-04T09:23:19Z","abstract_excerpt":"We present a novel decentralized algorithm for coverage control in unknown spatial environments modeled by Gaussian Processes (GPs). To trade-off between exploration and exploitation, each agent autonomously determines its trajectory by minimizing a local cost function. Inspired by the GP-UCB (Upper Confidence Bound for GPs) acquisition function, the proposed cost combines the expected locational cost with a variance-based exploration term, guiding agents toward regions that are both high in predicted density and model uncertainty. Compared to previous work, our algorithm operates in a fully d"},"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":"2511.02398","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-11-04T09:23:19Z","cross_cats_sorted":[],"title_canon_sha256":"43c990d35e8670f41e31dea35e78fe1ad316366a3f4fc869f35d2e866c84eb87","abstract_canon_sha256":"993dc4e4a9d5b7377c14a9a7890ecfac79c7852f1ce4f35a2aa2ad5b6a0ed744"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-28T02:04:44.146895Z","signature_b64":"NC/oEgD1mlwQBxyzgMNIyOaDYlKW7tYABquHK6srPgTJoVb6L8ySrBpqoigLk77AIBw9VfneeYCggnUwCSJxDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7fa170dc6f85f196e0044299de9e285218d3573df9c5ee772e6138055edacc1f","last_reissued_at":"2026-05-28T02:04:44.146371Z","signature_status":"signed_v1","first_computed_at":"2026-05-28T02:04:44.146371Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Spatially Informed Gaussian Process UCB Method for Decentralized Coverage Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Elia Raimondi, Florian D\\\"orfler, Gennaro Guidone, Han Wang, Luca Monegaglia, Mattia Bianchi","submitted_at":"2025-11-04T09:23:19Z","abstract_excerpt":"We present a novel decentralized algorithm for coverage control in unknown spatial environments modeled by Gaussian Processes (GPs). To trade-off between exploration and exploitation, each agent autonomously determines its trajectory by minimizing a local cost function. Inspired by the GP-UCB (Upper Confidence Bound for GPs) acquisition function, the proposed cost combines the expected locational cost with a variance-based exploration term, guiding agents toward regions that are both high in predicted density and model uncertainty. Compared to previous work, our algorithm operates in a fully d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.02398","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/2511.02398/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":"2511.02398","created_at":"2026-05-28T02:04:44.146439+00:00"},{"alias_kind":"arxiv_version","alias_value":"2511.02398v2","created_at":"2026-05-28T02:04:44.146439+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.02398","created_at":"2026-05-28T02:04:44.146439+00:00"},{"alias_kind":"pith_short_12","alias_value":"P6QXBXDPQXYZ","created_at":"2026-05-28T02:04:44.146439+00:00"},{"alias_kind":"pith_short_16","alias_value":"P6QXBXDPQXYZNYAE","created_at":"2026-05-28T02:04:44.146439+00:00"},{"alias_kind":"pith_short_8","alias_value":"P6QXBXDP","created_at":"2026-05-28T02:04:44.146439+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/P6QXBXDPQXYZNYAEIKM55HRIKI","json":"https://pith.science/pith/P6QXBXDPQXYZNYAEIKM55HRIKI.json","graph_json":"https://pith.science/api/pith-number/P6QXBXDPQXYZNYAEIKM55HRIKI/graph.json","events_json":"https://pith.science/api/pith-number/P6QXBXDPQXYZNYAEIKM55HRIKI/events.json","paper":"https://pith.science/paper/P6QXBXDP"},"agent_actions":{"view_html":"https://pith.science/pith/P6QXBXDPQXYZNYAEIKM55HRIKI","download_json":"https://pith.science/pith/P6QXBXDPQXYZNYAEIKM55HRIKI.json","view_paper":"https://pith.science/paper/P6QXBXDP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2511.02398&json=true","fetch_graph":"https://pith.science/api/pith-number/P6QXBXDPQXYZNYAEIKM55HRIKI/graph.json","fetch_events":"https://pith.science/api/pith-number/P6QXBXDPQXYZNYAEIKM55HRIKI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/P6QXBXDPQXYZNYAEIKM55HRIKI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/P6QXBXDPQXYZNYAEIKM55HRIKI/action/storage_attestation","attest_author":"https://pith.science/pith/P6QXBXDPQXYZNYAEIKM55HRIKI/action/author_attestation","sign_citation":"https://pith.science/pith/P6QXBXDPQXYZNYAEIKM55HRIKI/action/citation_signature","submit_replication":"https://pith.science/pith/P6QXBXDPQXYZNYAEIKM55HRIKI/action/replication_record"}},"created_at":"2026-05-28T02:04:44.146439+00:00","updated_at":"2026-05-28T02:04:44.146439+00:00"}