{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:A6XLWRU5WO2SUP7JAHHT63AGFU","short_pith_number":"pith:A6XLWRU5","schema_version":"1.0","canonical_sha256":"07aebb469db3b52a3fe901cf3f6c062d18086daf096c91f427e8d34302c6988b","source":{"kind":"arxiv","id":"2607.05957","version":1},"attestation_state":"computed","paper":{"title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"cs.RO","authors_text":"David Hyunchul Shim, Seungwook Lee","submitted_at":"2026-07-07T07:58:13Z","abstract_excerpt":"Multi-agent active visual triangulation enables precise 3D localization of aerial targets by coordinating mobile observers with controllable cameras. However, existing methods assume instantaneous state feedback, ignoring cumulative latency from detection, communication, and decision propagation. We present a delay-aware, uncertainty-driven multi-agent reinforcement learning framework for target localization in Counter-UAS applications. Our contributions are: (1) a Dec-POMDP formulation with Age-of-Information (AoI) augmented observations enabling delay-aware coordination -- AoI improves trian"},"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":"2607.05957","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2026-07-07T07:58:13Z","cross_cats_sorted":["cs.MA"],"title_canon_sha256":"d4de2066d0a0878c128b61db6d60654e4cdf77ef0fc14bea7c8b7509edbf5530","abstract_canon_sha256":"adcadc27a73796db02360c0a95888d7a5d461d70f3ec68c14a9584ed4ac85e3d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-08T01:18:51.635717Z","signature_b64":"pGRPLMZ4jRWrzYr25iul94ahTXoF8k/H3XN3qmMDdp/UagTVnhNSWFLCgew46h/rEbMyIT/+k2Qfa7UZSEPgBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"07aebb469db3b52a3fe901cf3f6c062d18086daf096c91f427e8d34302c6988b","last_reissued_at":"2026-07-08T01:18:51.635280Z","signature_status":"signed_v1","first_computed_at":"2026-07-08T01:18:51.635280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Delay-Aware Active Triangulation with Uncertainty-Driven Multi-Agent Reinforcement Learning for Counter-UAS","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"cs.RO","authors_text":"David Hyunchul Shim, Seungwook Lee","submitted_at":"2026-07-07T07:58:13Z","abstract_excerpt":"Multi-agent active visual triangulation enables precise 3D localization of aerial targets by coordinating mobile observers with controllable cameras. However, existing methods assume instantaneous state feedback, ignoring cumulative latency from detection, communication, and decision propagation. We present a delay-aware, uncertainty-driven multi-agent reinforcement learning framework for target localization in Counter-UAS applications. Our contributions are: (1) a Dec-POMDP formulation with Age-of-Information (AoI) augmented observations enabling delay-aware coordination -- AoI improves trian"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.05957","kind":"arxiv","version":1},"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/2607.05957/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":"2607.05957","created_at":"2026-07-08T01:18:51.635338+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.05957v1","created_at":"2026-07-08T01:18:51.635338+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.05957","created_at":"2026-07-08T01:18:51.635338+00:00"},{"alias_kind":"pith_short_12","alias_value":"A6XLWRU5WO2S","created_at":"2026-07-08T01:18:51.635338+00:00"},{"alias_kind":"pith_short_16","alias_value":"A6XLWRU5WO2SUP7J","created_at":"2026-07-08T01:18:51.635338+00:00"},{"alias_kind":"pith_short_8","alias_value":"A6XLWRU5","created_at":"2026-07-08T01:18:51.635338+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/A6XLWRU5WO2SUP7JAHHT63AGFU","json":"https://pith.science/pith/A6XLWRU5WO2SUP7JAHHT63AGFU.json","graph_json":"https://pith.science/api/pith-number/A6XLWRU5WO2SUP7JAHHT63AGFU/graph.json","events_json":"https://pith.science/api/pith-number/A6XLWRU5WO2SUP7JAHHT63AGFU/events.json","paper":"https://pith.science/paper/A6XLWRU5"},"agent_actions":{"view_html":"https://pith.science/pith/A6XLWRU5WO2SUP7JAHHT63AGFU","download_json":"https://pith.science/pith/A6XLWRU5WO2SUP7JAHHT63AGFU.json","view_paper":"https://pith.science/paper/A6XLWRU5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.05957&json=true","fetch_graph":"https://pith.science/api/pith-number/A6XLWRU5WO2SUP7JAHHT63AGFU/graph.json","fetch_events":"https://pith.science/api/pith-number/A6XLWRU5WO2SUP7JAHHT63AGFU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A6XLWRU5WO2SUP7JAHHT63AGFU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A6XLWRU5WO2SUP7JAHHT63AGFU/action/storage_attestation","attest_author":"https://pith.science/pith/A6XLWRU5WO2SUP7JAHHT63AGFU/action/author_attestation","sign_citation":"https://pith.science/pith/A6XLWRU5WO2SUP7JAHHT63AGFU/action/citation_signature","submit_replication":"https://pith.science/pith/A6XLWRU5WO2SUP7JAHHT63AGFU/action/replication_record"}},"created_at":"2026-07-08T01:18:51.635338+00:00","updated_at":"2026-07-08T01:18:51.635338+00:00"}