{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:AF6Q2G6VE7BG3QA2KM6FSCOPUS","short_pith_number":"pith:AF6Q2G6V","canonical_record":{"source":{"id":"1610.06204","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-10-19T20:29:20Z","cross_cats_sorted":[],"title_canon_sha256":"9bea822f778dd023fb9cfda29aca48d757c2c9355451342b3e7fa160bd6ed199","abstract_canon_sha256":"2ca3c564b7d153ae155116c5bc88e1e72850990214ff781c7dfc7ffcf4922de2"},"schema_version":"1.0"},"canonical_sha256":"017d0d1bd527c26dc01a533c5909cfa485cc8c0216d787591153636f4af84989","source":{"kind":"arxiv","id":"1610.06204","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1610.06204","created_at":"2026-05-18T00:57:43Z"},{"alias_kind":"arxiv_version","alias_value":"1610.06204v2","created_at":"2026-05-18T00:57:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.06204","created_at":"2026-05-18T00:57:43Z"},{"alias_kind":"pith_short_12","alias_value":"AF6Q2G6VE7BG","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AF6Q2G6VE7BG3QA2","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AF6Q2G6V","created_at":"2026-05-18T12:30:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:AF6Q2G6VE7BG3QA2KM6FSCOPUS","target":"record","payload":{"canonical_record":{"source":{"id":"1610.06204","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-10-19T20:29:20Z","cross_cats_sorted":[],"title_canon_sha256":"9bea822f778dd023fb9cfda29aca48d757c2c9355451342b3e7fa160bd6ed199","abstract_canon_sha256":"2ca3c564b7d153ae155116c5bc88e1e72850990214ff781c7dfc7ffcf4922de2"},"schema_version":"1.0"},"canonical_sha256":"017d0d1bd527c26dc01a533c5909cfa485cc8c0216d787591153636f4af84989","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:57:43.696276Z","signature_b64":"oxCczhnMp1hdcFO3vvlSt1OYhEl8/msu8FeV00hJNCBWBcvKwoUAj4L+YE2twTDCXNBPI32ANPTw0r45i2c5DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"017d0d1bd527c26dc01a533c5909cfa485cc8c0216d787591153636f4af84989","last_reissued_at":"2026-05-18T00:57:43.695886Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:57:43.695886Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1610.06204","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:57:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WlnMXh95hwxE7LZlaZu6ts6GquyglbQIedMrEe+wsNrMJQR8AbDjSjvA2qCglSHnkqi2SHTMWdGqhl8Yrj7HDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T05:44:39.986396Z"},"content_sha256":"7890846d381c2d6465217022d651ca177ad4008c657af7d14c5acd4b60f2a8f9","schema_version":"1.0","event_id":"sha256:7890846d381c2d6465217022d651ca177ad4008c657af7d14c5acd4b60f2a8f9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:AF6Q2G6VE7BG3QA2KM6FSCOPUS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Reinforcement Learning Approach to the View Planning Problem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Mustafa Devrim Kaba, Mustafa Gokhan Uzunbas, Ser Nam Lim","submitted_at":"2016-10-19T20:29:20Z","abstract_excerpt":"We present a Reinforcement Learning (RL) solution to the view planning problem (VPP), which generates a sequence of view points that are capable of sensing all accessible area of a given object represented as a 3D model. In doing so, the goal is to minimize the number of view points, making the VPP a class of set covering optimization problem (SCOP). The SCOP is NP-hard, and the inapproximability results tell us that the greedy algorithm provides the best approximation that runs in polynomial time. In order to find a solution that is better than the greedy algorithm, (i) we introduce a novel s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.06204","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":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:57:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+Y8fdddpPDLWq46oUL67pptC7eCM71vreattehSmba+G5K0BlyLIiV433NiJwitJFcrLBjkIanN9lOTzDQskBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T05:44:39.986746Z"},"content_sha256":"7a48522bc4cb5c4b87501b6f66276197f7924e08933c9a3582896553949892d8","schema_version":"1.0","event_id":"sha256:7a48522bc4cb5c4b87501b6f66276197f7924e08933c9a3582896553949892d8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AF6Q2G6VE7BG3QA2KM6FSCOPUS/bundle.json","state_url":"https://pith.science/pith/AF6Q2G6VE7BG3QA2KM6FSCOPUS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AF6Q2G6VE7BG3QA2KM6FSCOPUS/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-27T05:44:39Z","links":{"resolver":"https://pith.science/pith/AF6Q2G6VE7BG3QA2KM6FSCOPUS","bundle":"https://pith.science/pith/AF6Q2G6VE7BG3QA2KM6FSCOPUS/bundle.json","state":"https://pith.science/pith/AF6Q2G6VE7BG3QA2KM6FSCOPUS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AF6Q2G6VE7BG3QA2KM6FSCOPUS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:AF6Q2G6VE7BG3QA2KM6FSCOPUS","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":"2ca3c564b7d153ae155116c5bc88e1e72850990214ff781c7dfc7ffcf4922de2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-10-19T20:29:20Z","title_canon_sha256":"9bea822f778dd023fb9cfda29aca48d757c2c9355451342b3e7fa160bd6ed199"},"schema_version":"1.0","source":{"id":"1610.06204","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1610.06204","created_at":"2026-05-18T00:57:43Z"},{"alias_kind":"arxiv_version","alias_value":"1610.06204v2","created_at":"2026-05-18T00:57:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.06204","created_at":"2026-05-18T00:57:43Z"},{"alias_kind":"pith_short_12","alias_value":"AF6Q2G6VE7BG","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_16","alias_value":"AF6Q2G6VE7BG3QA2","created_at":"2026-05-18T12:30:07Z"},{"alias_kind":"pith_short_8","alias_value":"AF6Q2G6V","created_at":"2026-05-18T12:30:07Z"}],"graph_snapshots":[{"event_id":"sha256:7a48522bc4cb5c4b87501b6f66276197f7924e08933c9a3582896553949892d8","target":"graph","created_at":"2026-05-18T00:57:43Z","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"},"paper":{"abstract_excerpt":"We present a Reinforcement Learning (RL) solution to the view planning problem (VPP), which generates a sequence of view points that are capable of sensing all accessible area of a given object represented as a 3D model. In doing so, the goal is to minimize the number of view points, making the VPP a class of set covering optimization problem (SCOP). The SCOP is NP-hard, and the inapproximability results tell us that the greedy algorithm provides the best approximation that runs in polynomial time. In order to find a solution that is better than the greedy algorithm, (i) we introduce a novel s","authors_text":"Mustafa Devrim Kaba, Mustafa Gokhan Uzunbas, Ser Nam Lim","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-10-19T20:29:20Z","title":"A Reinforcement Learning Approach to the View Planning Problem"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.06204","kind":"arxiv","version":2},"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":"sha256:7890846d381c2d6465217022d651ca177ad4008c657af7d14c5acd4b60f2a8f9","target":"record","created_at":"2026-05-18T00:57:43Z","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":"2ca3c564b7d153ae155116c5bc88e1e72850990214ff781c7dfc7ffcf4922de2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-10-19T20:29:20Z","title_canon_sha256":"9bea822f778dd023fb9cfda29aca48d757c2c9355451342b3e7fa160bd6ed199"},"schema_version":"1.0","source":{"id":"1610.06204","kind":"arxiv","version":2}},"canonical_sha256":"017d0d1bd527c26dc01a533c5909cfa485cc8c0216d787591153636f4af84989","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"017d0d1bd527c26dc01a533c5909cfa485cc8c0216d787591153636f4af84989","first_computed_at":"2026-05-18T00:57:43.695886Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:57:43.695886Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oxCczhnMp1hdcFO3vvlSt1OYhEl8/msu8FeV00hJNCBWBcvKwoUAj4L+YE2twTDCXNBPI32ANPTw0r45i2c5DQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:57:43.696276Z","signed_message":"canonical_sha256_bytes"},"source_id":"1610.06204","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7890846d381c2d6465217022d651ca177ad4008c657af7d14c5acd4b60f2a8f9","sha256:7a48522bc4cb5c4b87501b6f66276197f7924e08933c9a3582896553949892d8"],"state_sha256":"1be5d27be9fed1fa475ba155a5bf513c4c94466b1accffba6de613336d6b4c47"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TtBvluZUpSvlB83i7LGWEJVc4MVjkHnizuDqRsdX3E9TlE9Sf3gyaUQSa4zfOyuOcuRzNbk0TIzf9vudhQpCAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T05:44:39.988677Z","bundle_sha256":"71cce1af444a963919609e74e6d112ccf98a398207dc73031881d3b43d88b16e"}}