{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:NBH4IB35FKUOSELQEIODV4UXF3","short_pith_number":"pith:NBH4IB35","schema_version":"1.0","canonical_sha256":"684fc4077d2aa8e91170221c3af2972ec9076f14af3a3e74cf216e150e1d0d6e","source":{"kind":"arxiv","id":"2408.16307","version":3},"attestation_state":"computed","paper":{"title":"Safe Bayesian Optimization for Complex Control Systems via Additive Gaussian Processes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Adrish Bhaumik, Hongxuan Wang, Lihao Zheng, Prahlad Vadakkepat, Xiaocong Li","submitted_at":"2024-08-29T07:12:37Z","abstract_excerpt":"Automatic controller tuning is attractive for robotics and mechatronic systems whose dynamics are difficult to model accurately, but direct black-box optimization can be unsafe because each query is executed on the physical plant. Existing safe Bayesian optimization (BO) methods provide high-probability safety guarantees, yet their practical use in multi-loop control is limited by two coupled difficulties: the controller parameter space is often moderately high-dimensional, and hardware evaluations are too expensive to allow hundreds or thousands of exploratory trials. This paper proposes \\tex"},"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":"2408.16307","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-08-29T07:12:37Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9769621b548cf5191463ccb1a7bb61d7fa16878bca1e9da5ab0eb8d0fa9c717e","abstract_canon_sha256":"65c25c63afd8f99916fea5fd7af80d93182cf4590cc7417bba1b76acd188dfc9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:05.044128Z","signature_b64":"pC9RI4VY0adZKRg4eR0fcDK4CxBqWLGv4sMNCbQOLp7spVaghvW/gHzaSRWgp2gASNSNE8oK8Lqw5ynB549cCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"684fc4077d2aa8e91170221c3af2972ec9076f14af3a3e74cf216e150e1d0d6e","last_reissued_at":"2026-05-17T23:39:05.043424Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:05.043424Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Safe Bayesian Optimization for Complex Control Systems via Additive Gaussian Processes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Adrish Bhaumik, Hongxuan Wang, Lihao Zheng, Prahlad Vadakkepat, Xiaocong Li","submitted_at":"2024-08-29T07:12:37Z","abstract_excerpt":"Automatic controller tuning is attractive for robotics and mechatronic systems whose dynamics are difficult to model accurately, but direct black-box optimization can be unsafe because each query is executed on the physical plant. Existing safe Bayesian optimization (BO) methods provide high-probability safety guarantees, yet their practical use in multi-loop control is limited by two coupled difficulties: the controller parameter space is often moderately high-dimensional, and hardware evaluations are too expensive to allow hundreds or thousands of exploratory trials. This paper proposes \\tex"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.16307","kind":"arxiv","version":3},"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":"2408.16307","created_at":"2026-05-17T23:39:05.043530+00:00"},{"alias_kind":"arxiv_version","alias_value":"2408.16307v3","created_at":"2026-05-17T23:39:05.043530+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.16307","created_at":"2026-05-17T23:39:05.043530+00:00"},{"alias_kind":"pith_short_12","alias_value":"NBH4IB35FKUO","created_at":"2026-05-18T12:33:37.589309+00:00"},{"alias_kind":"pith_short_16","alias_value":"NBH4IB35FKUOSELQ","created_at":"2026-05-18T12:33:37.589309+00:00"},{"alias_kind":"pith_short_8","alias_value":"NBH4IB35","created_at":"2026-05-18T12:33:37.589309+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/NBH4IB35FKUOSELQEIODV4UXF3","json":"https://pith.science/pith/NBH4IB35FKUOSELQEIODV4UXF3.json","graph_json":"https://pith.science/api/pith-number/NBH4IB35FKUOSELQEIODV4UXF3/graph.json","events_json":"https://pith.science/api/pith-number/NBH4IB35FKUOSELQEIODV4UXF3/events.json","paper":"https://pith.science/paper/NBH4IB35"},"agent_actions":{"view_html":"https://pith.science/pith/NBH4IB35FKUOSELQEIODV4UXF3","download_json":"https://pith.science/pith/NBH4IB35FKUOSELQEIODV4UXF3.json","view_paper":"https://pith.science/paper/NBH4IB35","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2408.16307&json=true","fetch_graph":"https://pith.science/api/pith-number/NBH4IB35FKUOSELQEIODV4UXF3/graph.json","fetch_events":"https://pith.science/api/pith-number/NBH4IB35FKUOSELQEIODV4UXF3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NBH4IB35FKUOSELQEIODV4UXF3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NBH4IB35FKUOSELQEIODV4UXF3/action/storage_attestation","attest_author":"https://pith.science/pith/NBH4IB35FKUOSELQEIODV4UXF3/action/author_attestation","sign_citation":"https://pith.science/pith/NBH4IB35FKUOSELQEIODV4UXF3/action/citation_signature","submit_replication":"https://pith.science/pith/NBH4IB35FKUOSELQEIODV4UXF3/action/replication_record"}},"created_at":"2026-05-17T23:39:05.043530+00:00","updated_at":"2026-05-17T23:39:05.043530+00:00"}