{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:PYMYAZD7LDK5CKK4EDHEMOLHWZ","short_pith_number":"pith:PYMYAZD7","schema_version":"1.0","canonical_sha256":"7e1980647f58d5d1295c20ce463967b66002993c2a417527f625b06357b340f2","source":{"kind":"arxiv","id":"2412.17992","version":1},"attestation_state":"computed","paper":{"title":"Falsification of Autonomous Systems in Rich Environments","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Khen Elimelech, Lydia E. Kavraki, Morteza Lahijanian, Moshe Y. Vardi","submitted_at":"2024-12-23T21:26:06Z","abstract_excerpt":"Validating the behavior of autonomous Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) agents, which rely on automated controllers, is an objective of great importance. In recent years, Neural-Network (NN) controllers have been demonstrating great promise. Unfortunately, such learned controllers are often not certified and can cause the system to suffer from unpredictable or unsafe behavior. To mitigate this issue, a great effort has been dedicated to automated verification of systems. Specifically, works in the category of ``black-box testing'' rely on repeated system simulations"},"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":"2412.17992","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-12-23T21:26:06Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"7b6e8b782d787d8e4637384fd5f8e11d9e7399a83cb4b4bbe3e56f87b325e8a9","abstract_canon_sha256":"91cea443809b42eaa1e4c5173dc94852aff23b4fee986789542bbcdd07bceb1c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:53:32.012270Z","signature_b64":"di6mFEmpoExjN4Df1icBvVxFHTRrzgVoqujgAizLBMgtEfuzc3NkyVPIwAxSLOVvilh2QF6tfVGA7EDuh0wrBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7e1980647f58d5d1295c20ce463967b66002993c2a417527f625b06357b340f2","last_reissued_at":"2026-07-05T09:53:32.011933Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:53:32.011933Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Falsification of Autonomous Systems in Rich Environments","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Khen Elimelech, Lydia E. Kavraki, Morteza Lahijanian, Moshe Y. Vardi","submitted_at":"2024-12-23T21:26:06Z","abstract_excerpt":"Validating the behavior of autonomous Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) agents, which rely on automated controllers, is an objective of great importance. In recent years, Neural-Network (NN) controllers have been demonstrating great promise. Unfortunately, such learned controllers are often not certified and can cause the system to suffer from unpredictable or unsafe behavior. To mitigate this issue, a great effort has been dedicated to automated verification of systems. Specifically, works in the category of ``black-box testing'' rely on repeated system simulations"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.17992","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2412.17992/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2412.17992","created_at":"2026-07-05T09:53:32.011988+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.17992v1","created_at":"2026-07-05T09:53:32.011988+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.17992","created_at":"2026-07-05T09:53:32.011988+00:00"},{"alias_kind":"pith_short_12","alias_value":"PYMYAZD7LDK5","created_at":"2026-07-05T09:53:32.011988+00:00"},{"alias_kind":"pith_short_16","alias_value":"PYMYAZD7LDK5CKK4","created_at":"2026-07-05T09:53:32.011988+00:00"},{"alias_kind":"pith_short_8","alias_value":"PYMYAZD7","created_at":"2026-07-05T09:53:32.011988+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.17703","citing_title":"Piecewise Control Barrier Functions for Stochastic Systems","ref_index":6,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PYMYAZD7LDK5CKK4EDHEMOLHWZ","json":"https://pith.science/pith/PYMYAZD7LDK5CKK4EDHEMOLHWZ.json","graph_json":"https://pith.science/api/pith-number/PYMYAZD7LDK5CKK4EDHEMOLHWZ/graph.json","events_json":"https://pith.science/api/pith-number/PYMYAZD7LDK5CKK4EDHEMOLHWZ/events.json","paper":"https://pith.science/paper/PYMYAZD7"},"agent_actions":{"view_html":"https://pith.science/pith/PYMYAZD7LDK5CKK4EDHEMOLHWZ","download_json":"https://pith.science/pith/PYMYAZD7LDK5CKK4EDHEMOLHWZ.json","view_paper":"https://pith.science/paper/PYMYAZD7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.17992&json=true","fetch_graph":"https://pith.science/api/pith-number/PYMYAZD7LDK5CKK4EDHEMOLHWZ/graph.json","fetch_events":"https://pith.science/api/pith-number/PYMYAZD7LDK5CKK4EDHEMOLHWZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PYMYAZD7LDK5CKK4EDHEMOLHWZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PYMYAZD7LDK5CKK4EDHEMOLHWZ/action/storage_attestation","attest_author":"https://pith.science/pith/PYMYAZD7LDK5CKK4EDHEMOLHWZ/action/author_attestation","sign_citation":"https://pith.science/pith/PYMYAZD7LDK5CKK4EDHEMOLHWZ/action/citation_signature","submit_replication":"https://pith.science/pith/PYMYAZD7LDK5CKK4EDHEMOLHWZ/action/replication_record"}},"created_at":"2026-07-05T09:53:32.011988+00:00","updated_at":"2026-07-05T09:53:32.011988+00:00"}