{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:J7MO4KIWLCS7YAD6GEV54OTEPP","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":"88ddd817437d4fde354006431737636f6c2d479918f9a16d069d0e578873c2c2","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-12-15T17:19:35Z","title_canon_sha256":"a2e73f64a2f53b792eb7424c49bb3bf6dd3fbb69a0f4585eba3202dc7910278b"},"schema_version":"1.0","source":{"id":"1812.06325","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.06325","created_at":"2026-05-17T23:55:42Z"},{"alias_kind":"arxiv_version","alias_value":"1812.06325v2","created_at":"2026-05-17T23:55:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.06325","created_at":"2026-05-17T23:55:42Z"},{"alias_kind":"pith_short_12","alias_value":"J7MO4KIWLCS7","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"J7MO4KIWLCS7YAD6","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"J7MO4KIW","created_at":"2026-05-18T12:32:31Z"}],"graph_snapshots":[{"event_id":"sha256:071ef40f462d5db5f3edfaded9a7a3e5d5098ec2e6db70dedcc89a6d51e415bc","target":"graph","created_at":"2026-05-17T23:55:42Z","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"},"paper":{"abstract_excerpt":"Bayesian optimization is proposed for automatic learning of optimal controller parameters from experimental data. A probabilistic description (a Gaussian process) is used to model the unknown function from controller parameters to a user-defined cost. The probabilistic model is updated with data, which is obtained by testing a set of parameters on the physical system and evaluating the cost. In order to learn fast, the Bayesian optimization algorithm selects the next parameters to evaluate in a systematic way, for example, by maximizing information gain about the optimum. The algorithm thus it","authors_text":"Alonso Marco, Dieter Schwarzmann, Matthias Neumann-Brosig, Sebastian Trimpe","cross_cats":["cs.LG","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-12-15T17:19:35Z","title":"Data-efficient Auto-tuning with Bayesian Optimization: An Industrial Control Study"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.06325","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":"sha256:2d7f0f23478f65c85a10ba2af6f3e10229c6b057328ec832a789fa56c065fa44","target":"record","created_at":"2026-05-17T23:55:42Z","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":"88ddd817437d4fde354006431737636f6c2d479918f9a16d069d0e578873c2c2","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-12-15T17:19:35Z","title_canon_sha256":"a2e73f64a2f53b792eb7424c49bb3bf6dd3fbb69a0f4585eba3202dc7910278b"},"schema_version":"1.0","source":{"id":"1812.06325","kind":"arxiv","version":2}},"canonical_sha256":"4fd8ee291658a5fc007e312bde3a647bea48f226d5612daffc1887f51e491123","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4fd8ee291658a5fc007e312bde3a647bea48f226d5612daffc1887f51e491123","first_computed_at":"2026-05-17T23:55:42.361081Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:55:42.361081Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yjZYjjdZd36zJBfdtg867H+TgIPElLi0CCQPEm3Pk0SnHN+BRvaqmJTDbAaBjd+FC7B3ZABXuSkHiuqlhs58DA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:55:42.361519Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.06325","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2d7f0f23478f65c85a10ba2af6f3e10229c6b057328ec832a789fa56c065fa44","sha256:071ef40f462d5db5f3edfaded9a7a3e5d5098ec2e6db70dedcc89a6d51e415bc"],"state_sha256":"d5701079df593cf86104fdc2b95a52ac79b9c737944b519e81fde3363b6909b5"}