{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:BFBWF2PSUZH5P427OOJE3Z6L4G","short_pith_number":"pith:BFBWF2PS","schema_version":"1.0","canonical_sha256":"094362e9f2a64fd7f35f73924de7cbe19dc8dcf4ace7d03e639b7949820f4285","source":{"kind":"arxiv","id":"1210.2452","version":1},"attestation_state":"computed","paper":{"title":"Learn with SAT to Minimize B\\\"uchi Automata","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.FL","authors_text":"Martin Hofmann, Stephan Barth","submitted_at":"2012-10-09T00:53:36Z","abstract_excerpt":"We describe a minimization procedure for nondeterministic B\\\"uchi automata (NBA). For an automaton A another automaton A_min with the minimal number of states  is learned with the help of a SAT-solver.\n  This is done by successively computing automata A' that approximate A in the  sense that they accept a given finite set of positive examples and reject a  given finite set of negative examples. In the course of the procedure these example sets are successively increased. Thus, our method can be seen as an  instance of a generic learning algorithm based on a \"minimally adequate  teacher\" in the"},"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":"1210.2452","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.FL","submitted_at":"2012-10-09T00:53:36Z","cross_cats_sorted":[],"title_canon_sha256":"39f600028702b9ce67769927defe9a8c1523e6508473ab09167a6a63fe423b52","abstract_canon_sha256":"fe6e1de9c08bbe219494ecbea618d78bf57bc60606da8c43052cd4da257e779c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:43:41.498731Z","signature_b64":"CpXmws5yQhsLOYitp5z9MJ8lFip2DG+8g7tHNw6j1XPNCuNEfXLq/U1meQI84pUZy41MOC96ItrjzPkefEZLBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"094362e9f2a64fd7f35f73924de7cbe19dc8dcf4ace7d03e639b7949820f4285","last_reissued_at":"2026-05-18T03:43:41.498130Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:43:41.498130Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learn with SAT to Minimize B\\\"uchi Automata","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.FL","authors_text":"Martin Hofmann, Stephan Barth","submitted_at":"2012-10-09T00:53:36Z","abstract_excerpt":"We describe a minimization procedure for nondeterministic B\\\"uchi automata (NBA). For an automaton A another automaton A_min with the minimal number of states  is learned with the help of a SAT-solver.\n  This is done by successively computing automata A' that approximate A in the  sense that they accept a given finite set of positive examples and reject a  given finite set of negative examples. In the course of the procedure these example sets are successively increased. Thus, our method can be seen as an  instance of a generic learning algorithm based on a \"minimally adequate  teacher\" in the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1210.2452","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1210.2452","created_at":"2026-05-18T03:43:41.498230+00:00"},{"alias_kind":"arxiv_version","alias_value":"1210.2452v1","created_at":"2026-05-18T03:43:41.498230+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1210.2452","created_at":"2026-05-18T03:43:41.498230+00:00"},{"alias_kind":"pith_short_12","alias_value":"BFBWF2PSUZH5","created_at":"2026-05-18T12:26:58.693483+00:00"},{"alias_kind":"pith_short_16","alias_value":"BFBWF2PSUZH5P427","created_at":"2026-05-18T12:26:58.693483+00:00"},{"alias_kind":"pith_short_8","alias_value":"BFBWF2PS","created_at":"2026-05-18T12:26:58.693483+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/BFBWF2PSUZH5P427OOJE3Z6L4G","json":"https://pith.science/pith/BFBWF2PSUZH5P427OOJE3Z6L4G.json","graph_json":"https://pith.science/api/pith-number/BFBWF2PSUZH5P427OOJE3Z6L4G/graph.json","events_json":"https://pith.science/api/pith-number/BFBWF2PSUZH5P427OOJE3Z6L4G/events.json","paper":"https://pith.science/paper/BFBWF2PS"},"agent_actions":{"view_html":"https://pith.science/pith/BFBWF2PSUZH5P427OOJE3Z6L4G","download_json":"https://pith.science/pith/BFBWF2PSUZH5P427OOJE3Z6L4G.json","view_paper":"https://pith.science/paper/BFBWF2PS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1210.2452&json=true","fetch_graph":"https://pith.science/api/pith-number/BFBWF2PSUZH5P427OOJE3Z6L4G/graph.json","fetch_events":"https://pith.science/api/pith-number/BFBWF2PSUZH5P427OOJE3Z6L4G/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BFBWF2PSUZH5P427OOJE3Z6L4G/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BFBWF2PSUZH5P427OOJE3Z6L4G/action/storage_attestation","attest_author":"https://pith.science/pith/BFBWF2PSUZH5P427OOJE3Z6L4G/action/author_attestation","sign_citation":"https://pith.science/pith/BFBWF2PSUZH5P427OOJE3Z6L4G/action/citation_signature","submit_replication":"https://pith.science/pith/BFBWF2PSUZH5P427OOJE3Z6L4G/action/replication_record"}},"created_at":"2026-05-18T03:43:41.498230+00:00","updated_at":"2026-05-18T03:43:41.498230+00:00"}