{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:SUTXRPOZAGIPVDIOHRD6LWZSZK","short_pith_number":"pith:SUTXRPOZ","schema_version":"1.0","canonical_sha256":"952778bdd90190fa8d0e3c47e5db32cab0b962bf71d34f80cbd7ae9fb9ab27f0","source":{"kind":"arxiv","id":"2503.02369","version":1},"attestation_state":"computed","paper":{"title":"JPDS-NN: Reinforcement Learning-Based Dynamic Task Allocation for Agricultural Vehicle Routing Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Haotian Xu, Mengqiao Liu, Qing Zhuo, Tao Zhang, Yixuan Fan","submitted_at":"2025-03-04T07:50:32Z","abstract_excerpt":"The Entrance Dependent Vehicle Routing Problem (EDVRP) is a variant of the Vehicle Routing Problem (VRP) where the scale of cities influences routing outcomes, necessitating consideration of their entrances. This paper addresses EDVRP in agriculture, focusing on multi-parameter vehicle planning for irregularly shaped fields. To address the limitations of traditional methods, such as heuristic approaches, which often overlook field geometry and entrance constraints, we propose a Joint Probability Distribution Sampling Neural Network (JPDS-NN) to effectively solve the EDVRP. The network uses an "},"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":"2503.02369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-04T07:50:32Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"49a38547c630cc9e247645c1a08c6afbd84f20a020de76466a148b0631ec5a6e","abstract_canon_sha256":"5e7e713f9b4c3850fb4e41b8e77f49e771b8c176c90040646ce1ac35af3494fd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:23:42.395942Z","signature_b64":"jsY8M/zhW/dJzngaiypH1sUDEqW+lzueaikh6y3D9xX6FSKG57plIzf+c6ZZC5dHLvOgKuBFmTIvt/krhXuLAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"952778bdd90190fa8d0e3c47e5db32cab0b962bf71d34f80cbd7ae9fb9ab27f0","last_reissued_at":"2026-07-05T10:23:42.395458Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:23:42.395458Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"JPDS-NN: Reinforcement Learning-Based Dynamic Task Allocation for Agricultural Vehicle Routing Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Haotian Xu, Mengqiao Liu, Qing Zhuo, Tao Zhang, Yixuan Fan","submitted_at":"2025-03-04T07:50:32Z","abstract_excerpt":"The Entrance Dependent Vehicle Routing Problem (EDVRP) is a variant of the Vehicle Routing Problem (VRP) where the scale of cities influences routing outcomes, necessitating consideration of their entrances. This paper addresses EDVRP in agriculture, focusing on multi-parameter vehicle planning for irregularly shaped fields. To address the limitations of traditional methods, such as heuristic approaches, which often overlook field geometry and entrance constraints, we propose a Joint Probability Distribution Sampling Neural Network (JPDS-NN) to effectively solve the EDVRP. The network uses an "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.02369","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/2503.02369/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":"2503.02369","created_at":"2026-07-05T10:23:42.395518+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.02369v1","created_at":"2026-07-05T10:23:42.395518+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.02369","created_at":"2026-07-05T10:23:42.395518+00:00"},{"alias_kind":"pith_short_12","alias_value":"SUTXRPOZAGIP","created_at":"2026-07-05T10:23:42.395518+00:00"},{"alias_kind":"pith_short_16","alias_value":"SUTXRPOZAGIPVDIO","created_at":"2026-07-05T10:23:42.395518+00:00"},{"alias_kind":"pith_short_8","alias_value":"SUTXRPOZ","created_at":"2026-07-05T10:23:42.395518+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/SUTXRPOZAGIPVDIOHRD6LWZSZK","json":"https://pith.science/pith/SUTXRPOZAGIPVDIOHRD6LWZSZK.json","graph_json":"https://pith.science/api/pith-number/SUTXRPOZAGIPVDIOHRD6LWZSZK/graph.json","events_json":"https://pith.science/api/pith-number/SUTXRPOZAGIPVDIOHRD6LWZSZK/events.json","paper":"https://pith.science/paper/SUTXRPOZ"},"agent_actions":{"view_html":"https://pith.science/pith/SUTXRPOZAGIPVDIOHRD6LWZSZK","download_json":"https://pith.science/pith/SUTXRPOZAGIPVDIOHRD6LWZSZK.json","view_paper":"https://pith.science/paper/SUTXRPOZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.02369&json=true","fetch_graph":"https://pith.science/api/pith-number/SUTXRPOZAGIPVDIOHRD6LWZSZK/graph.json","fetch_events":"https://pith.science/api/pith-number/SUTXRPOZAGIPVDIOHRD6LWZSZK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SUTXRPOZAGIPVDIOHRD6LWZSZK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SUTXRPOZAGIPVDIOHRD6LWZSZK/action/storage_attestation","attest_author":"https://pith.science/pith/SUTXRPOZAGIPVDIOHRD6LWZSZK/action/author_attestation","sign_citation":"https://pith.science/pith/SUTXRPOZAGIPVDIOHRD6LWZSZK/action/citation_signature","submit_replication":"https://pith.science/pith/SUTXRPOZAGIPVDIOHRD6LWZSZK/action/replication_record"}},"created_at":"2026-07-05T10:23:42.395518+00:00","updated_at":"2026-07-05T10:23:42.395518+00:00"}