{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:3CVMZGZOJMZFRKQPSCCZOBO7B7","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":"1ced76d8565bb58cc32435d176a751c4e0bed8ca25d90a76c3627cf47bfd2b8c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-03T16:08:40Z","title_canon_sha256":"42cd92e9af93fb2259a98e5a61585ac669d67e61aec63fd35e826c6ecab2f20d"},"schema_version":"1.0","source":{"id":"2211.02052","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.02052","created_at":"2026-07-05T05:17:02Z"},{"alias_kind":"arxiv_version","alias_value":"2211.02052v2","created_at":"2026-07-05T05:17:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.02052","created_at":"2026-07-05T05:17:02Z"},{"alias_kind":"pith_short_12","alias_value":"3CVMZGZOJMZF","created_at":"2026-07-05T05:17:02Z"},{"alias_kind":"pith_short_16","alias_value":"3CVMZGZOJMZFRKQP","created_at":"2026-07-05T05:17:02Z"},{"alias_kind":"pith_short_8","alias_value":"3CVMZGZO","created_at":"2026-07-05T05:17:02Z"}],"graph_snapshots":[{"event_id":"sha256:ca275df1edf1797e1077fc2c18f2c38c28d0e260399c3562a466e8147faf6866","target":"graph","created_at":"2026-07-05T05:17:02Z","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/2211.02052/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Given an environment (e.g., a simulator) for evaluating samples in a specified design space and a set of weighted evaluation metrics -- one can use Theta-Resonance, a single-step Markov Decision Process (MDP), to train an intelligent agent producing progressively more optimal samples. In Theta-Resonance, a neural network consumes a constant input tensor and produces a policy as a set of conditional probability density functions (PDFs) for sampling each design dimension. We specialize existing policy gradient algorithms in deep reinforcement learning (D-RL) in order to use evaluation feedback (","authors_text":"Masood S. Mortazavi, Ning Yan, Tiancheng Qin","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-03T16:08:40Z","title":"Theta-Resonance: A Single-Step Reinforcement Learning Method for Design Space Exploration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.02052","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":"sha256:2e06c8365e13b6c64a6431373c7225af06f23ca8194581d8e1e2f86a23ed5f50","target":"record","created_at":"2026-07-05T05:17:02Z","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":"1ced76d8565bb58cc32435d176a751c4e0bed8ca25d90a76c3627cf47bfd2b8c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-03T16:08:40Z","title_canon_sha256":"42cd92e9af93fb2259a98e5a61585ac669d67e61aec63fd35e826c6ecab2f20d"},"schema_version":"1.0","source":{"id":"2211.02052","kind":"arxiv","version":2}},"canonical_sha256":"d8aacc9b2e4b3258aa0f90859705df0fe962b23c7f9cf95756dc188a043d9c90","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d8aacc9b2e4b3258aa0f90859705df0fe962b23c7f9cf95756dc188a043d9c90","first_computed_at":"2026-07-05T05:17:02.710774Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:17:02.710774Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EsMBQSs5xQ8U9cLA6iwr+1xROM6bXOhiqfdkeJaFLrj/hfieWPXXMD2RqKtbOG99ea8x/HNZUx5CpLSF9dT0CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:17:02.711243Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.02052","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2e06c8365e13b6c64a6431373c7225af06f23ca8194581d8e1e2f86a23ed5f50","sha256:ca275df1edf1797e1077fc2c18f2c38c28d0e260399c3562a466e8147faf6866"],"state_sha256":"1274f1a86fed0b5ee6a9ef77ad5e14d460d6b2bb06c10fb3988fa16dd1c4937b"}