{"id":"https://openalex.org/W7166880552","doi":"https://doi.org/10.48550/arxiv.2606.31025","title":"Offline Reinforcement Learning for Fluid Controls: Data-based Multi-observational Policy Extraction","display_name":"Offline Reinforcement Learning for Fluid Controls: Data-based Multi-observational Policy Extraction","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7166880552","doi":"https://doi.org/10.48550/arxiv.2606.31025"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.31025","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31025","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2606.31025","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139826560","display_name":"Deepak Akhare","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akhare, Deepak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121042310","display_name":"L G Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Luning","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042389036","display_name":"Xin\u2010Yang Liu","orcid":"https://orcid.org/0000-0003-1423-605X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Xin-Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072978635","display_name":"Xiantao Fan","orcid":"https://orcid.org/0000-0002-0977-0330"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Xiantao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099981475","display_name":"Timo Bremer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bremer, Timo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104279611","display_name":"B X Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Ben","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139829919","display_name":"Jian-Xun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Jian-Xun","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":0.6366999745368958,"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":0.6366999745368958,"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/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.11029999703168869,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.08139999955892563,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.826200008392334},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.659600019454956},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.439300000667572},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.42800000309944153},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.4058000147342682},{"id":"https://openalex.org/keywords/intelligent-sensor","display_name":"Intelligent sensor","score":0.35010001063346863},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.34060001373291016},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.3393000066280365},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3310000002384186}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.826200008392334},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.659600019454956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6474000215530396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5062000155448914},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.439300000667572},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.42800000309944153},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.4058000147342682},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37450000643730164},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.3711000084877014},{"id":"https://openalex.org/C176563091","wikidata":"https://www.wikidata.org/wiki/Q669238","display_name":"Intelligent sensor","level":3,"score":0.35010001063346863},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.34060001373291016},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.3393000066280365},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3310000002384186},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C82327864","wikidata":"https://www.wikidata.org/wiki/Q835100","display_name":"Intelligent control","level":2,"score":0.3125},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.30630001425743103},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C186766456","wikidata":"https://www.wikidata.org/wiki/Q612457","display_name":"Flow control (data)","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2782000005245209},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.2648000121116638},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C2780490138","wikidata":"https://www.wikidata.org/wiki/Q7079636","display_name":"Offline learning","level":3,"score":0.25189998745918274},{"id":"https://openalex.org/C2780102126","wikidata":"https://www.wikidata.org/wiki/Q10928179","display_name":"Online and offline","level":2,"score":0.25049999356269836},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.31025","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31025","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.31025","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.31025","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Active":[0],"flow":[1,127,162],"control":[2,128,163],"is":[3],"a":[4,61,76,82,156],"fundamental":[5],"application":[6],"in":[7,11,18,49,122],"engineering.":[8],"Recent":[9],"advances":[10],"deep":[12],"reinforcement":[13],"learning":[14],"have":[15],"made":[16],"progress":[17],"this":[19,57],"field.":[20],"However,":[21],"the":[22,32,106,114,123,133,140,144],"classical":[23],"online":[24],"RL":[25,64],"approaches":[26],"require":[27],"extensive":[28],"real-time":[29],"interactions":[30],"with":[31],"high":[33],"fidelity":[34],"environment,":[35],"while":[36],"each":[37],"sensor":[38,77,91,110,150],"configuration":[39],"change":[40],"necessitates":[41],"whole":[42],"policy":[43,72,84,141],"retraining.":[44],"All":[45],"these":[46],"factors":[47],"result":[48,137],"prohibitive":[50],"computational":[51],"costs":[52],"for":[53,149],"real-world":[54],"applications.":[55],"In":[56],"work,":[58],"we":[59],"propose":[60],"novel":[62],"offline":[63],"framework":[65,115],"that":[66,80,139],"addresses":[67],"both":[68],"challenges":[69],"through":[70,100],"data-driven":[71],"extraction.":[73],"We":[74,112],"develop":[75],"position-conditioned":[78,94],"architecture":[79],"enables":[81],"single":[83],"network":[85],"to":[86,89,104,108],"adapt":[87],"seamlessly":[88],"multiple":[90],"arrangements.":[92],"The":[93,136],"approach":[95,154],"incorporated":[96],"spatial":[97],"relationship":[98],"modeling":[99],"Point":[101],"Attention":[102],"layers":[103],"ensure":[105],"generalizability":[107],"varying":[109],"placements.":[111],"demonstrate":[113],"on":[116],"two":[117],"representative":[118],"problems,":[119],"mitigating":[120],"chaoticity":[121],"Kuramoto-Sivashinsky":[124],"equation":[125],"and":[126],"over":[129],"airfoils":[130],"governed":[131],"by":[132],"Navier-Stokes":[134],"equation.":[135],"demonstrates":[138],"extraction":[142],"from":[143],"dataset":[145],"provides":[146],"unprecedented":[147],"flexibility":[148],"placement":[151],"optimization.":[152],"This":[153],"represents":[155],"significant":[157],"step":[158],"towards":[159],"adaptive,":[160],"intelligent":[161],"systems.":[164]},"counts_by_year":[],"updated_date":"2026-07-02T06:18:51.028212","created_date":"2026-07-02T00:00:00"}
