{"id":"https://openalex.org/W2973184296","doi":"https://doi.org/10.1109/tnnls.2022.3168795","title":"Energy-Based Continuous Inverse Optimal Control","display_name":"Energy-Based Continuous Inverse Optimal Control","publication_year":2022,"publication_date":"2022-05-05","ids":{"openalex":"https://openalex.org/W2973184296","doi":"https://doi.org/10.1109/tnnls.2022.3168795","mag":"2973184296","pmid":"https://pubmed.ncbi.nlm.nih.gov/35511835"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3168795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3168795","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100781347","display_name":"Yifei Xu","orcid":"https://orcid.org/0000-0003-2407-3266"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yifei Xu","raw_affiliation_strings":["Department of Statistics, University of California at Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of California at Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102966958","display_name":"Jianwen Xie","orcid":"https://orcid.org/0000-0002-6818-7444"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]},{"id":"https://openalex.org/I4210159958","display_name":"Cognitive Research (United States)","ror":"https://ror.org/04s361q55","country_code":"US","type":"company","lineage":["https://openalex.org/I4210159958"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianwen Xie","raw_affiliation_strings":["Cognitive Computing Laboratory, Baidu Research, Bellevue, WA, USA"],"affiliations":[{"raw_affiliation_string":"Cognitive Computing Laboratory, Baidu Research, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210159958","https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101615684","display_name":"Tianyang Zhao","orcid":"https://orcid.org/0000-0001-9081-5753"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianyang Zhao","raw_affiliation_strings":["Department of Statistics, University of California at Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of California at Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108502488","display_name":"Chris Baker","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chris Baker","raw_affiliation_strings":["iSee, Inc., Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"iSee, Inc., Cambridge, MA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091164091","display_name":"Yibiao Zhao","orcid":"https://orcid.org/0000-0001-9517-1969"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yibiao Zhao","raw_affiliation_strings":["iSee, Inc., Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"iSee, Inc., Cambridge, MA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101780958","display_name":"Ying Wu","orcid":"https://orcid.org/0009-0001-6768-5118"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ying Nian Wu","raw_affiliation_strings":["Department of Statistics, University of California at Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of California at Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100781347"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":1.1104,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.80592647,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"34","issue":"12","first_page":"10563","last_page":"10577"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9907000064849854,"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"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9757999777793884,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5774841904640198},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.5770885348320007},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5768262147903442},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.5549767017364502},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5537810325622559},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.545412003993988},{"id":"https://openalex.org/keywords/iterated-function","display_name":"Iterated function","score":0.5111749768257141},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.47623422741889954},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4539903402328491},{"id":"https://openalex.org/keywords/trajectory-optimization","display_name":"Trajectory optimization","score":0.43419256806373596},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42385879158973694},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33578482270240784},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3131684362888336},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.18221724033355713}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5774841904640198},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.5770885348320007},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5768262147903442},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5549767017364502},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5537810325622559},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.545412003993988},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.5111749768257141},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.47623422741889954},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4539903402328491},{"id":"https://openalex.org/C173246807","wikidata":"https://www.wikidata.org/wiki/Q7833062","display_name":"Trajectory optimization","level":3,"score":0.43419256806373596},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42385879158973694},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33578482270240784},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3131684362888336},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.18221724033355713},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3168795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3168795","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35511835","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35511835","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G3381030244","display_name":null,"funder_award_id":"W911NF-16-1-0579","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G4211722790","display_name":null,"funder_award_id":"N00014-16-1-2007","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G4215934209","display_name":null,"funder_award_id":"DMS-2015577","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6606814275","display_name":null,"funder_award_id":"N66001-17-2-4029","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G7135109975","display_name":null,"funder_award_id":"N66001-15-C-4035","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":89,"referenced_works":["https://openalex.org/W195033972","https://openalex.org/W1505878979","https://openalex.org/W1522301498","https://openalex.org/W1527702126","https://openalex.org/W1538131130","https://openalex.org/W1677182931","https://openalex.org/W1771410628","https://openalex.org/W1929981607","https://openalex.org/W1977970897","https://openalex.org/W1993170675","https://openalex.org/W1994616650","https://openalex.org/W2023443487","https://openalex.org/W2072195747","https://openalex.org/W2098774185","https://openalex.org/W2099111195","https://openalex.org/W2099471712","https://openalex.org/W2116064496","https://openalex.org/W2138309709","https://openalex.org/W2150920547","https://openalex.org/W2163605009","https://openalex.org/W2188585002","https://openalex.org/W2194775991","https://openalex.org/W2342840547","https://openalex.org/W2403419699","https://openalex.org/W2424778531","https://openalex.org/W2478027467","https://openalex.org/W2566467060","https://openalex.org/W2580495915","https://openalex.org/W2587460705","https://openalex.org/W2607296803","https://openalex.org/W2616635592","https://openalex.org/W2621006664","https://openalex.org/W2736601468","https://openalex.org/W2745467776","https://openalex.org/W2750866482","https://openalex.org/W2766836212","https://openalex.org/W2768629321","https://openalex.org/W2784715585","https://openalex.org/W2788289427","https://openalex.org/W2803332797","https://openalex.org/W2806124528","https://openalex.org/W2809461852","https://openalex.org/W2810677299","https://openalex.org/W2940129212","https://openalex.org/W2949457404","https://openalex.org/W2950465931","https://openalex.org/W2954040150","https://openalex.org/W2962687116","https://openalex.org/W2963001155","https://openalex.org/W2963140844","https://openalex.org/W2963219401","https://openalex.org/W2963277051","https://openalex.org/W2963328631","https://openalex.org/W2963590100","https://openalex.org/W2964335397","https://openalex.org/W2965615945","https://openalex.org/W2967195040","https://openalex.org/W2967593122","https://openalex.org/W2998058414","https://openalex.org/W2998462233","https://openalex.org/W3004970274","https://openalex.org/W3104946437","https://openalex.org/W3105115779","https://openalex.org/W3112740951","https://openalex.org/W3116874393","https://openalex.org/W3138435543","https://openalex.org/W3146928245","https://openalex.org/W3174370604","https://openalex.org/W3175924964","https://openalex.org/W4241470522","https://openalex.org/W4241749978","https://openalex.org/W6631190155","https://openalex.org/W6632100814","https://openalex.org/W6635084905","https://openalex.org/W6638018090","https://openalex.org/W6638440308","https://openalex.org/W6640443443","https://openalex.org/W6640963894","https://openalex.org/W6674884181","https://openalex.org/W6681286327","https://openalex.org/W6684191040","https://openalex.org/W6694077575","https://openalex.org/W6696380822","https://openalex.org/W6714644935","https://openalex.org/W6718092244","https://openalex.org/W6731259203","https://openalex.org/W6741002519","https://openalex.org/W6746462176","https://openalex.org/W6838767951"],"related_works":["https://openalex.org/W3106461837","https://openalex.org/W3103325625","https://openalex.org/W1486898455","https://openalex.org/W4364381099","https://openalex.org/W3168182983","https://openalex.org/W4321472004","https://openalex.org/W4387079005","https://openalex.org/W4283700523","https://openalex.org/W2003479292","https://openalex.org/W3135469233"],"abstract_inverted_index":{"The":[0,73],"problem":[1,35],"of":[2,21,39,63,75,155,207],"continuous":[3,22],"inverse":[4],"optimal":[5,146,229],"control":[6,23,147],"(over":[7],"finite":[8],"time":[9,111],"horizon)":[10],"is":[11,141,199],"to":[12,50,69,172,182,201],"learn":[13,224],"the":[14,19,37,44,61,64,76,96,100,105,117,122,126,130,134,156,163,166,174,184,196,204,208,212],"unknown":[15],"cost":[16,66,77,226],"function":[17,58,67,78],"over":[18],"sequence":[20],"variables":[24],"from":[25,54,99],"expert":[26,46],"demonstrations.":[27],"In":[28],"this":[29,33],"article,":[30],"we":[31,149,161,180],"study":[32],"fundamental":[34],"in":[36,165],"framework":[38],"energy-based":[40],"model":[41,118],"(EBM),":[42],"where":[43,160,195],"observed":[45,131],"trajectories":[47,98,128],"are":[48,79],"assumed":[49],"be":[51],"random":[52],"samples":[53],"a":[55,70,152,188],"probability":[56,102],"density":[57,103],"defined":[59],"as":[60],"exponential":[62],"negative":[65],"up":[68],"normalizing":[71],"constant.":[72],"parameters":[74,119],"learned":[80],"by":[81,87,169],"maximum":[82],"likelihood":[83],"via":[84,108,192],"an":[85,137,145],"\"analysis":[86],"synthesis\"":[88],"scheme,":[89],"which":[90],"iterates:":[91],"1)":[92],"synthesis":[93,167,205],"step:":[94,115],"sample":[95],"synthesized":[97,127],"current":[101],"using":[104],"Langevin":[106],"dynamics":[107],"backpropagation":[109],"through":[110],"and":[112,129,219],"2)":[113],"analysis":[114],"update":[116],"based":[120],"on":[121,215],"statistical":[123],"difference":[124],"between":[125],"trajectories.":[132],"Given":[133],"fact":[135],"that":[136,221],"efficient":[138],"optimization":[139,177],"algorithm":[140],"usually":[142],"available":[143],"for":[144,228],"problem,":[148],"also":[150],"consider":[151],"convenient":[153],"approximation":[154],"above":[157],"learning":[158],"method,":[159],"replace":[162],"sampling":[164,175],"step":[168,206],"optimization.":[170],"Moreover,":[171],"make":[173],"or":[176],"more":[178],"efficient,":[179],"propose":[181],"train":[183],"EBM":[185],"simultaneously":[186],"with":[187],"top-down":[189],"trajectory":[190,197],"generator":[191,198],"cooperative":[193],"learning,":[194],"used":[200],"fast":[202],"initialize":[203],"EBM.":[209],"We":[210],"demonstrate":[211],"proposed":[213],"methods":[214],"autonomous":[216],"driving":[217],"tasks":[218],"show":[220],"they":[222],"can":[223],"suitable":[225],"functions":[227],"control.":[230]},"counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}