{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:JDVGGVFN2KC6M7EHA3YPNRGK72","short_pith_number":"pith:JDVGGVFN","schema_version":"1.0","canonical_sha256":"48ea6354add285e67c8706f0f6c4cafe89c158d299ae2e0228e293c655276e21","source":{"kind":"arxiv","id":"2212.00862","version":1},"attestation_state":"computed","paper":{"title":"An introduction to optimization under uncertainty -- A short survey","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC","math.PR","stat.AP"],"primary_cat":"cs.AI","authors_text":"Calvin R. Hubbard, David Moens, Hans Hallez, Kaizheng Wang, Keivan Shariatmadar","submitted_at":"2022-12-01T20:48:06Z","abstract_excerpt":"Optimization equips engineers and scientists in a variety of fields with the ability to transcribe their problems into a generic formulation and receive optimal solutions with relative ease. Industries ranging from aerospace to robotics continue to benefit from advancements in optimization theory and the associated algorithmic developments. Nowadays, optimization is used in real time on autonomous systems acting in safety critical situations, such as self-driving vehicles. It has become increasingly more important to produce robust solutions by incorporating uncertainty into optimization progr"},"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":"2212.00862","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2022-12-01T20:48:06Z","cross_cats_sorted":["math.OC","math.PR","stat.AP"],"title_canon_sha256":"0e48b4e49aede03ce94af470858956a54ed6ac54457493257a348d3267f0f59b","abstract_canon_sha256":"52984fa615c719d943e00147fb1f8af6b54f18a31f7ca318ae4f3267fb736e1b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:21:46.581824Z","signature_b64":"dNWgTf/brx8KyVcToWysVR5YLuO5NFIqPSW89bJsmOQxfuvLghhbE21p7aPTqCS79sUqLMSYt277m0yXXt60Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"48ea6354add285e67c8706f0f6c4cafe89c158d299ae2e0228e293c655276e21","last_reissued_at":"2026-07-05T05:21:46.581352Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:21:46.581352Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An introduction to optimization under uncertainty -- A short survey","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.OC","math.PR","stat.AP"],"primary_cat":"cs.AI","authors_text":"Calvin R. Hubbard, David Moens, Hans Hallez, Kaizheng Wang, Keivan Shariatmadar","submitted_at":"2022-12-01T20:48:06Z","abstract_excerpt":"Optimization equips engineers and scientists in a variety of fields with the ability to transcribe their problems into a generic formulation and receive optimal solutions with relative ease. Industries ranging from aerospace to robotics continue to benefit from advancements in optimization theory and the associated algorithmic developments. Nowadays, optimization is used in real time on autonomous systems acting in safety critical situations, such as self-driving vehicles. It has become increasingly more important to produce robust solutions by incorporating uncertainty into optimization progr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.00862","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/2212.00862/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":"2212.00862","created_at":"2026-07-05T05:21:46.581410+00:00"},{"alias_kind":"arxiv_version","alias_value":"2212.00862v1","created_at":"2026-07-05T05:21:46.581410+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.00862","created_at":"2026-07-05T05:21:46.581410+00:00"},{"alias_kind":"pith_short_12","alias_value":"JDVGGVFN2KC6","created_at":"2026-07-05T05:21:46.581410+00:00"},{"alias_kind":"pith_short_16","alias_value":"JDVGGVFN2KC6M7EH","created_at":"2026-07-05T05:21:46.581410+00:00"},{"alias_kind":"pith_short_8","alias_value":"JDVGGVFN","created_at":"2026-07-05T05:21:46.581410+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/JDVGGVFN2KC6M7EHA3YPNRGK72","json":"https://pith.science/pith/JDVGGVFN2KC6M7EHA3YPNRGK72.json","graph_json":"https://pith.science/api/pith-number/JDVGGVFN2KC6M7EHA3YPNRGK72/graph.json","events_json":"https://pith.science/api/pith-number/JDVGGVFN2KC6M7EHA3YPNRGK72/events.json","paper":"https://pith.science/paper/JDVGGVFN"},"agent_actions":{"view_html":"https://pith.science/pith/JDVGGVFN2KC6M7EHA3YPNRGK72","download_json":"https://pith.science/pith/JDVGGVFN2KC6M7EHA3YPNRGK72.json","view_paper":"https://pith.science/paper/JDVGGVFN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2212.00862&json=true","fetch_graph":"https://pith.science/api/pith-number/JDVGGVFN2KC6M7EHA3YPNRGK72/graph.json","fetch_events":"https://pith.science/api/pith-number/JDVGGVFN2KC6M7EHA3YPNRGK72/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JDVGGVFN2KC6M7EHA3YPNRGK72/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JDVGGVFN2KC6M7EHA3YPNRGK72/action/storage_attestation","attest_author":"https://pith.science/pith/JDVGGVFN2KC6M7EHA3YPNRGK72/action/author_attestation","sign_citation":"https://pith.science/pith/JDVGGVFN2KC6M7EHA3YPNRGK72/action/citation_signature","submit_replication":"https://pith.science/pith/JDVGGVFN2KC6M7EHA3YPNRGK72/action/replication_record"}},"created_at":"2026-07-05T05:21:46.581410+00:00","updated_at":"2026-07-05T05:21:46.581410+00:00"}