{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:RI6VBDLC5ORKGKPJ3IF4KQ5SKB","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":"18516e25d2c307a9b61f69ac7bc7b0465bff7a66557dc9c611e2a49ce2d4a6bc","cross_cats_sorted":["cs.NE"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-05-18T07:01:58Z","title_canon_sha256":"3b96007b7c22ae10036c0a8df2d28101010d4db5673b78d0d547aaa1c7610161"},"schema_version":"1.0","source":{"id":"2305.10760","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.10760","created_at":"2026-07-05T06:11:26Z"},{"alias_kind":"arxiv_version","alias_value":"2305.10760v1","created_at":"2026-07-05T06:11:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.10760","created_at":"2026-07-05T06:11:26Z"},{"alias_kind":"pith_short_12","alias_value":"RI6VBDLC5ORK","created_at":"2026-07-05T06:11:26Z"},{"alias_kind":"pith_short_16","alias_value":"RI6VBDLC5ORKGKPJ","created_at":"2026-07-05T06:11:26Z"},{"alias_kind":"pith_short_8","alias_value":"RI6VBDLC","created_at":"2026-07-05T06:11:26Z"}],"graph_snapshots":[{"event_id":"sha256:bd64529b12414d1c2c94bbcd1164007f8905ea8343e84a08fa27de856ac7d58e","target":"graph","created_at":"2026-07-05T06:11:26Z","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/2305.10760/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The layout design of pipelines is a critical task in the construction industry. Currently, pipeline layout is designed manually by engineers, which is time-consuming and laborious. Automating and streamlining this process can reduce the burden on engineers and save time. In this paper, we propose a method for generating three-dimensional layout of pipelines based on deep reinforcement learning (DRL). Firstly, we abstract the geometric features of space to establish a training environment and define reward functions based on three constraints: pipeline length, elbow, and installation distance. ","authors_text":"Chen Yang, Jia-Rui Lin, Zhe Zheng","cross_cats":["cs.NE"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-05-18T07:01:58Z","title":"Automatic Design Method of Building Pipeline Layout Based on Deep Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.10760","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":"sha256:8aae7561afd820367e870d96e4aee669e17939f0d4701c84b972bd9634399262","target":"record","created_at":"2026-07-05T06:11:26Z","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":"18516e25d2c307a9b61f69ac7bc7b0465bff7a66557dc9c611e2a49ce2d4a6bc","cross_cats_sorted":["cs.NE"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-05-18T07:01:58Z","title_canon_sha256":"3b96007b7c22ae10036c0a8df2d28101010d4db5673b78d0d547aaa1c7610161"},"schema_version":"1.0","source":{"id":"2305.10760","kind":"arxiv","version":1}},"canonical_sha256":"8a3d508d62eba2a329e9da0bc543b25043eeb891e818a542345041356059c431","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a3d508d62eba2a329e9da0bc543b25043eeb891e818a542345041356059c431","first_computed_at":"2026-07-05T06:11:26.273838Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:11:26.273838Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kE5avJ/fsdFZgWyCA9sInVyfEBQXzkSlQuxY5I/X/dvIpXs1P1x6TorztCD4tyH4/4rbQjVQtXgzYrDJI04CDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:11:26.274358Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.10760","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8aae7561afd820367e870d96e4aee669e17939f0d4701c84b972bd9634399262","sha256:bd64529b12414d1c2c94bbcd1164007f8905ea8343e84a08fa27de856ac7d58e"],"state_sha256":"8c10c2d16503fc911f90c0e7b4e0ebe4fc4914b66f0d37c69fcd887dea6ee7bd"}