{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:4UZNWTRQN3CFHTPB3VIIO3CJM6","short_pith_number":"pith:4UZNWTRQ","canonical_record":{"source":{"id":"1906.02578","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-06-06T13:35:49Z","cross_cats_sorted":[],"title_canon_sha256":"cdb1944576d11479164c35836b18a5ffa349311eb492cea1a6db8061893c1bb0","abstract_canon_sha256":"4081170f0a18047e58f8731b91d0ba7db482c5f858822c668192f74d421ddfe5"},"schema_version":"1.0"},"canonical_sha256":"e532db4e306ec453cde1dd50876c4967b883ba5492b7e18605982b8a22cfebb9","source":{"kind":"arxiv","id":"1906.02578","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.02578","created_at":"2026-05-17T23:44:00Z"},{"alias_kind":"arxiv_version","alias_value":"1906.02578v1","created_at":"2026-05-17T23:44:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.02578","created_at":"2026-05-17T23:44:00Z"},{"alias_kind":"pith_short_12","alias_value":"4UZNWTRQN3CF","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4UZNWTRQN3CFHTPB","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4UZNWTRQ","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:4UZNWTRQN3CFHTPB3VIIO3CJM6","target":"record","payload":{"canonical_record":{"source":{"id":"1906.02578","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-06-06T13:35:49Z","cross_cats_sorted":[],"title_canon_sha256":"cdb1944576d11479164c35836b18a5ffa349311eb492cea1a6db8061893c1bb0","abstract_canon_sha256":"4081170f0a18047e58f8731b91d0ba7db482c5f858822c668192f74d421ddfe5"},"schema_version":"1.0"},"canonical_sha256":"e532db4e306ec453cde1dd50876c4967b883ba5492b7e18605982b8a22cfebb9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:00.713766Z","signature_b64":"bcnp1HUmMeNgUdkCUZh1HXpzKJDIV8pa4AADrU3pzzb5EZDsjAMiR9pjDglp4U3v0w8r10JMYxRHPfyjFNBoDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e532db4e306ec453cde1dd50876c4967b883ba5492b7e18605982b8a22cfebb9","last_reissued_at":"2026-05-17T23:44:00.713073Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:00.713073Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.02578","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S3QFAHN8rvlvif4/Thg5ecQMUbX9A7/H86oHYPu5R8BOTTrmZrmRcPIrFah4RioSVP7jfN/Crwn0KeveBl5MAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T03:53:10.848524Z"},"content_sha256":"0ac3d038882ed618a6dfeaba6e17f9b1d7d0325ebf334b4aece8e7e0d5f1059d","schema_version":"1.0","event_id":"sha256:0ac3d038882ed618a6dfeaba6e17f9b1d7d0325ebf334b4aece8e7e0d5f1059d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:4UZNWTRQN3CFHTPB3VIIO3CJM6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Combining Reinforcement Learning and Configuration Checking for Maximum k-plex Problem","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Hai Wan, Jia Li, Peilin Chen, Shaowei Cai, Weilin Luo","submitted_at":"2019-06-06T13:35:49Z","abstract_excerpt":"The Maximum k-plex Problem is an important combinatorial optimization problem with increasingly wide applications. Due to its exponential time complexity, many heuristic methods have been proposed which can return a good-quality solution in a reasonable time. However, most of the heuristic algorithms are memoryless and unable to utilize the experience during the search. Inspired by the multi-armed bandit (MAB) problem in reinforcement learning (RL), we propose a novel perturbation mechanism named BLP, which can learn online to select a good vertex for perturbation when getting stuck in local o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.02578","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":""},"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":"2026-05-17T23:44:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1lrOO4ujECjwBFZhviWmhjhxKjOZw/wzFDkaX0uvMvjSN304qY1GjTvL/kDLSvI4uF7/3m5m3DGEku+GcHliDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T03:53:10.849026Z"},"content_sha256":"79f77fc8ae6ea8846ccd97048f7053562dcb08070cfe9bfa8136162e74770eec","schema_version":"1.0","event_id":"sha256:79f77fc8ae6ea8846ccd97048f7053562dcb08070cfe9bfa8136162e74770eec"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4UZNWTRQN3CFHTPB3VIIO3CJM6/bundle.json","state_url":"https://pith.science/pith/4UZNWTRQN3CFHTPB3VIIO3CJM6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4UZNWTRQN3CFHTPB3VIIO3CJM6/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":"2026-05-26T03:53:10Z","links":{"resolver":"https://pith.science/pith/4UZNWTRQN3CFHTPB3VIIO3CJM6","bundle":"https://pith.science/pith/4UZNWTRQN3CFHTPB3VIIO3CJM6/bundle.json","state":"https://pith.science/pith/4UZNWTRQN3CFHTPB3VIIO3CJM6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4UZNWTRQN3CFHTPB3VIIO3CJM6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4UZNWTRQN3CFHTPB3VIIO3CJM6","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":"4081170f0a18047e58f8731b91d0ba7db482c5f858822c668192f74d421ddfe5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-06-06T13:35:49Z","title_canon_sha256":"cdb1944576d11479164c35836b18a5ffa349311eb492cea1a6db8061893c1bb0"},"schema_version":"1.0","source":{"id":"1906.02578","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.02578","created_at":"2026-05-17T23:44:00Z"},{"alias_kind":"arxiv_version","alias_value":"1906.02578v1","created_at":"2026-05-17T23:44:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.02578","created_at":"2026-05-17T23:44:00Z"},{"alias_kind":"pith_short_12","alias_value":"4UZNWTRQN3CF","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4UZNWTRQN3CFHTPB","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4UZNWTRQ","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:79f77fc8ae6ea8846ccd97048f7053562dcb08070cfe9bfa8136162e74770eec","target":"graph","created_at":"2026-05-17T23:44:00Z","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":"The Maximum k-plex Problem is an important combinatorial optimization problem with increasingly wide applications. Due to its exponential time complexity, many heuristic methods have been proposed which can return a good-quality solution in a reasonable time. However, most of the heuristic algorithms are memoryless and unable to utilize the experience during the search. Inspired by the multi-armed bandit (MAB) problem in reinforcement learning (RL), we propose a novel perturbation mechanism named BLP, which can learn online to select a good vertex for perturbation when getting stuck in local o","authors_text":"Hai Wan, Jia Li, Peilin Chen, Shaowei Cai, Weilin Luo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-06-06T13:35:49Z","title":"Combining Reinforcement Learning and Configuration Checking for Maximum k-plex Problem"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.02578","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":"sha256:0ac3d038882ed618a6dfeaba6e17f9b1d7d0325ebf334b4aece8e7e0d5f1059d","target":"record","created_at":"2026-05-17T23:44:00Z","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":"4081170f0a18047e58f8731b91d0ba7db482c5f858822c668192f74d421ddfe5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2019-06-06T13:35:49Z","title_canon_sha256":"cdb1944576d11479164c35836b18a5ffa349311eb492cea1a6db8061893c1bb0"},"schema_version":"1.0","source":{"id":"1906.02578","kind":"arxiv","version":1}},"canonical_sha256":"e532db4e306ec453cde1dd50876c4967b883ba5492b7e18605982b8a22cfebb9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e532db4e306ec453cde1dd50876c4967b883ba5492b7e18605982b8a22cfebb9","first_computed_at":"2026-05-17T23:44:00.713073Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:00.713073Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bcnp1HUmMeNgUdkCUZh1HXpzKJDIV8pa4AADrU3pzzb5EZDsjAMiR9pjDglp4U3v0w8r10JMYxRHPfyjFNBoDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:00.713766Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.02578","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ac3d038882ed618a6dfeaba6e17f9b1d7d0325ebf334b4aece8e7e0d5f1059d","sha256:79f77fc8ae6ea8846ccd97048f7053562dcb08070cfe9bfa8136162e74770eec"],"state_sha256":"07a709cbb6d799409d9180d33065e3b4c82bcfb006afe218b6355f299cb0822d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0kRrPZTF7nq/StRnbGY8iIO4XqUv6duI1rcfUhPXdLvSzH+66MNUr9gFRX6KPu4vkc2J/wEKI18HSHUHZxRqCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T03:53:10.852372Z","bundle_sha256":"88bbbccd8702daf4f4fb572ddc8c6a323e15c5000adefd4a8e43ca7db35cb73f"}}