{"id":"https://openalex.org/W7154626918","doi":"https://doi.org/10.48550/arxiv.2604.13673","title":"Behavioral Systems Theory Meets Machine Learning: Control-Aware Learning of the Intrinsic Behavior from Big Data","display_name":"Behavioral Systems Theory Meets Machine Learning: Control-Aware Learning of the Intrinsic Behavior from Big Data","publication_year":2026,"publication_date":"2026-04-15","ids":{"openalex":"https://openalex.org/W7154626918","doi":"https://doi.org/10.48550/arxiv.2604.13673"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.13673","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13673","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.13673","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065332258","display_name":"Yitao Yan","orcid":"https://orcid.org/0000-0002-3329-2615"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan, Yitao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133764338","display_name":"Yu Tong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133820175","display_name":"Jie Bao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bao, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5055712317","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0003-3901-8403"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.26269999146461487,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.26269999146461487,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.2371000051498413,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.053300000727176666,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5605000257492065},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.5056999921798706},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47589999437332153},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4726000130176544},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4438000023365021},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4108000099658966},{"id":"https://openalex.org/keywords/learning-theory","display_name":"Learning theory","score":0.4025999903678894},{"id":"https://openalex.org/keywords/computational-learning-theory","display_name":"Computational learning theory","score":0.39089998602867126},{"id":"https://openalex.org/keywords/control-system","display_name":"Control system","score":0.36230000853538513}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.65420001745224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6345000267028809},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5605000257492065},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.5056999921798706},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47589999437332153},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4726000130176544},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47209998965263367},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4108000099658966},{"id":"https://openalex.org/C92393732","wikidata":"https://www.wikidata.org/wiki/Q1790374","display_name":"Learning theory","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C50292564","wikidata":"https://www.wikidata.org/wiki/Q2462783","display_name":"Computational learning theory","level":3,"score":0.39089998602867126},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C32254414","wikidata":"https://www.wikidata.org/wiki/Q4724364","display_name":"Algorithmic learning theory","level":3,"score":0.3504999876022339},{"id":"https://openalex.org/C79379906","wikidata":"https://www.wikidata.org/wiki/Q3174497","display_name":"Dynamical systems theory","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C129537906","wikidata":"https://www.wikidata.org/wiki/Q7603913","display_name":"State variable","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C24138899","wikidata":"https://www.wikidata.org/wiki/Q17141258","display_name":"Instance-based learning","level":3,"score":0.29339998960494995},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C82327864","wikidata":"https://www.wikidata.org/wiki/Q835100","display_name":"Intelligent control","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.26269999146461487},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C78639753","wikidata":"https://www.wikidata.org/wiki/Q3318160","display_name":"Behavioral modeling","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.13673","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13673","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.13673","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13673","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.41135895252227783,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"abundance":[1],"of":[2,14,39,56,68,134],"process":[3],"operating":[4],"data":[5],"in":[6,92],"modern":[7],"industries,":[8],"along":[9],"with":[10,32],"the":[11,50,62,74,89,107,115,136],"rapid":[12],"advancement":[13],"learning":[15,31,71,122,135],"techniques,":[16],"has":[17],"led":[18],"to":[19,126],"a":[20,43,93,127],"paradigm":[21],"shift":[22],"towards":[23],"data-centric":[24],"analysis":[25],"and":[26,53,65,95,98],"control.":[27],"However,":[28],"integrating":[29],"machine":[30,121],"control":[33,38,58,99,141],"theory":[34,59],"for":[35,140],"big":[36,69],"data-driven":[37],"nonlinear":[40],"systems":[41,81],"remains":[42],"challenging":[44],"open":[45],"problem.":[46],"This":[47,110],"is":[48,132],"because":[49],"state-based,":[51],"model-centric,":[52],"causal":[54],"framework":[55],"classical":[57],"fundamentally":[60],"contradicts":[61],"trajectory-based,":[63],"set-theoretic,":[64],"causality-absent":[66],"rationale":[67],"data-based":[70],"approaches.":[72],"Using":[73],"behavioral":[75],"framework,":[76],"we":[77],"show":[78],"that":[79,87,131],"dynamical":[80],"possess":[82],"an":[83],"intrinsic":[84],"state":[85,108],"variable":[86],"encodes":[88],"system":[90],"behavior":[91,137],"bijective":[94],"causality-free":[96],"manner,":[97],"design":[100],"can":[101],"be":[102],"carried":[103],"out":[104],"entirely":[105],"within":[106],"space.":[109],"approach":[111],"not":[112],"only":[113],"resolves":[114],"aforementioned":[116],"conflict":[117],"but":[118],"also":[119],"complements":[120],"techniques":[123],"well,":[124],"leading":[125],"neural":[128],"network":[129],"architecture":[130],"capable":[133],"representation":[138],"well-suited":[139],"design.":[142]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-17T00:00:00"}
