{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:I2HBZMUUUQRC2XSUBCU6UX7VI7","short_pith_number":"pith:I2HBZMUU","schema_version":"1.0","canonical_sha256":"468e1cb294a4222d5e5408a9ea5ff547f82304b1c58756497fc78d3f51356f1c","source":{"kind":"arxiv","id":"2607.11344","version":1},"attestation_state":"computed","paper":{"title":"Learning to control switching nonlinear systems with Koopman operator regression","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY","eess.SY","stat.ML"],"primary_cat":"math.OC","authors_text":"Cesare Molinari, Edoardo Caldarelli, Lorenzo Rosasco, Oleksii Kachaiev","submitted_at":"2026-07-13T10:06:23Z","abstract_excerpt":"In this work, we consider the identification and control of nonlinear systems with finite action spaces. The unknown dynamics are estimated from finite samples with Koopman operator regression in a reproducing kernel Hilbert space, yielding a linear switching predictive model, the switches governed by the value of the control variable. In order to perform control in closed-loop, the learned dynamics are employed in an infinite-horizon optimal control problem with time-varying stage cost, which is solved by means of model predictive control. In a theoretical analysis, we derive learning rates f"},"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":"2607.11344","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2026-07-13T10:06:23Z","cross_cats_sorted":["cs.SY","eess.SY","stat.ML"],"title_canon_sha256":"2795c27944036191f8030064a1a33e32f65019081291ce8954d06f1833034d38","abstract_canon_sha256":"ac61945d307e39333d6e65bc8748c6c82c6c96df5f453637bd0ddbead112543a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-14T01:22:30.233708Z","signature_b64":"2zWy6zoeh3RMuVGClIt4Yt8IPGPuGzdKwSG2p8Ol9x8CjIe3GbMGpO/I0ONWFPrsOtz94/tuAU7/c4sR5wCoDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"468e1cb294a4222d5e5408a9ea5ff547f82304b1c58756497fc78d3f51356f1c","last_reissued_at":"2026-07-14T01:22:30.232813Z","signature_status":"signed_v1","first_computed_at":"2026-07-14T01:22:30.232813Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning to control switching nonlinear systems with Koopman operator regression","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY","eess.SY","stat.ML"],"primary_cat":"math.OC","authors_text":"Cesare Molinari, Edoardo Caldarelli, Lorenzo Rosasco, Oleksii Kachaiev","submitted_at":"2026-07-13T10:06:23Z","abstract_excerpt":"In this work, we consider the identification and control of nonlinear systems with finite action spaces. The unknown dynamics are estimated from finite samples with Koopman operator regression in a reproducing kernel Hilbert space, yielding a linear switching predictive model, the switches governed by the value of the control variable. In order to perform control in closed-loop, the learned dynamics are employed in an infinite-horizon optimal control problem with time-varying stage cost, which is solved by means of model predictive control. In a theoretical analysis, we derive learning rates f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.11344","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/2607.11344/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":"2607.11344","created_at":"2026-07-14T01:22:30.233260+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.11344v1","created_at":"2026-07-14T01:22:30.233260+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.11344","created_at":"2026-07-14T01:22:30.233260+00:00"},{"alias_kind":"pith_short_12","alias_value":"I2HBZMUUUQRC","created_at":"2026-07-14T01:22:30.233260+00:00"},{"alias_kind":"pith_short_16","alias_value":"I2HBZMUUUQRC2XSU","created_at":"2026-07-14T01:22:30.233260+00:00"},{"alias_kind":"pith_short_8","alias_value":"I2HBZMUU","created_at":"2026-07-14T01:22:30.233260+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/I2HBZMUUUQRC2XSUBCU6UX7VI7","json":"https://pith.science/pith/I2HBZMUUUQRC2XSUBCU6UX7VI7.json","graph_json":"https://pith.science/api/pith-number/I2HBZMUUUQRC2XSUBCU6UX7VI7/graph.json","events_json":"https://pith.science/api/pith-number/I2HBZMUUUQRC2XSUBCU6UX7VI7/events.json","paper":"https://pith.science/paper/I2HBZMUU"},"agent_actions":{"view_html":"https://pith.science/pith/I2HBZMUUUQRC2XSUBCU6UX7VI7","download_json":"https://pith.science/pith/I2HBZMUUUQRC2XSUBCU6UX7VI7.json","view_paper":"https://pith.science/paper/I2HBZMUU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.11344&json=true","fetch_graph":"https://pith.science/api/pith-number/I2HBZMUUUQRC2XSUBCU6UX7VI7/graph.json","fetch_events":"https://pith.science/api/pith-number/I2HBZMUUUQRC2XSUBCU6UX7VI7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I2HBZMUUUQRC2XSUBCU6UX7VI7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I2HBZMUUUQRC2XSUBCU6UX7VI7/action/storage_attestation","attest_author":"https://pith.science/pith/I2HBZMUUUQRC2XSUBCU6UX7VI7/action/author_attestation","sign_citation":"https://pith.science/pith/I2HBZMUUUQRC2XSUBCU6UX7VI7/action/citation_signature","submit_replication":"https://pith.science/pith/I2HBZMUUUQRC2XSUBCU6UX7VI7/action/replication_record"}},"created_at":"2026-07-14T01:22:30.233260+00:00","updated_at":"2026-07-14T01:22:30.233260+00:00"}