{"id":"https://openalex.org/W4385482619","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191211","title":"Uncertainty-Aware Data Augmentation for Offline Reinforcement Learning","display_name":"Uncertainty-Aware Data Augmentation for Offline Reinforcement Learning","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385482619","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191211"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191211","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5109778654","display_name":"Yunjie Su","orcid":null},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunjie Su","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University,Shenzhen,China","Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University,Shenzhen,China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023910710","display_name":"Yilun Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilun Kong","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University,Shenzhen,China","Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University,Shenzhen,China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100737125","display_name":"Xueqian Wang","orcid":"https://orcid.org/0000-0003-3542-0593"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueqian Wang","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University,Shenzhen,China","Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University,Shenzhen,China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]},{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2178,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42125523,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9994000196456909,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9994000196456909,"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/T10879","display_name":"Robotic Locomotion and Control","score":0.9696000218391418,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9674999713897705,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8345890641212463},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7407091856002808},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5707876682281494},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5492047667503357},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.511769711971283},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.49548137187957764},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4305473566055298},{"id":"https://openalex.org/keywords/temporal-difference-learning","display_name":"Temporal difference learning","score":0.423796147108078},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4126066565513611},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08158451318740845}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8345890641212463},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7407091856002808},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5707876682281494},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5492047667503357},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.511769711971283},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.49548137187957764},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4305473566055298},{"id":"https://openalex.org/C196340769","wikidata":"https://www.wikidata.org/wiki/Q7698910","display_name":"Temporal difference learning","level":3,"score":0.423796147108078},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4126066565513611},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08158451318740845},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191211","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn54540.2023.10191211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W582134693","https://openalex.org/W1945616565","https://openalex.org/W2111959010","https://openalex.org/W2112420033","https://openalex.org/W2158782408","https://openalex.org/W2257979135","https://openalex.org/W2600383743","https://openalex.org/W2773691349","https://openalex.org/W2781726626","https://openalex.org/W2787938642","https://openalex.org/W2807588596","https://openalex.org/W2904453761","https://openalex.org/W2947150733","https://openalex.org/W2949103145","https://openalex.org/W2954996726","https://openalex.org/W2963411833","https://openalex.org/W2971442502","https://openalex.org/W2982041329","https://openalex.org/W2991355586","https://openalex.org/W3008276149","https://openalex.org/W3015437096","https://openalex.org/W3016525976","https://openalex.org/W3021708257","https://openalex.org/W3022566517","https://openalex.org/W3033324992","https://openalex.org/W3088304681","https://openalex.org/W3115293622","https://openalex.org/W3118172322","https://openalex.org/W3125947392","https://openalex.org/W3170059879","https://openalex.org/W3172360140","https://openalex.org/W3176552394","https://openalex.org/W3201700917","https://openalex.org/W3211444363","https://openalex.org/W4285607107","https://openalex.org/W4287082344","https://openalex.org/W4288319859","https://openalex.org/W4298857966","https://openalex.org/W4311033368","https://openalex.org/W4360584316","https://openalex.org/W6617145748","https://openalex.org/W6637967152","https://openalex.org/W6640425456","https://openalex.org/W6677916085","https://openalex.org/W6733049761","https://openalex.org/W6735443497","https://openalex.org/W6744563498","https://openalex.org/W6746700722","https://openalex.org/W6747473740","https://openalex.org/W6748839928","https://openalex.org/W6752244597","https://openalex.org/W6757469721","https://openalex.org/W6763704811","https://openalex.org/W6764053384","https://openalex.org/W6767572230","https://openalex.org/W6769342953","https://openalex.org/W6771270455","https://openalex.org/W6776438516","https://openalex.org/W6776601253","https://openalex.org/W6776867236","https://openalex.org/W6779265984","https://openalex.org/W6779827379","https://openalex.org/W6782766965","https://openalex.org/W6791413555","https://openalex.org/W6795014841","https://openalex.org/W6796589144","https://openalex.org/W6798709053","https://openalex.org/W6803383913","https://openalex.org/W6804112224","https://openalex.org/W6810466897"],"related_works":["https://openalex.org/W4400868993","https://openalex.org/W2247996358","https://openalex.org/W2145363145","https://openalex.org/W2341346307","https://openalex.org/W2154399718","https://openalex.org/W4321463377","https://openalex.org/W4384574988","https://openalex.org/W2768629321","https://openalex.org/W1914583973","https://openalex.org/W2130711276"],"abstract_inverted_index":{"One":[0],"of":[1,22,34,37,79,91,120,128,134,146,154],"the":[2,32,38,47,57,60,74,77,83,88,92,102,113,117,121,126,129,135,144,150,155,188,197],"key":[3],"challenges":[4],"in":[5,20,42],"Offline":[6],"Reinforcement":[7],"Learning":[8],"is":[9,27,63,164],"that":[10,184],"it":[11],"cannot":[12],"conduct":[13],"further":[14],"environment":[15],"exploration":[16],"and":[17,87,115,152,172,190],"performs":[18],"poorly":[19],"terms":[21],"out-of-distribution":[23],"generalizations.":[24],"Data":[25,162],"augmentation":[26,50,147],"commonly":[28],"used":[29],"to":[30,100,112,124,142],"solve":[31],"issue":[33],"limited":[35,65],"coverage":[36,62],"full":[39],"state-action":[40],"space":[41],"static":[43,103],"offline":[44,104,169,176],"dataset.":[45],"However,":[46],"existing":[48],"data":[49,61],"methods":[51,71],"for":[52],"proprioceptive":[53],"observation":[54],"suffer":[55],"from":[56],"dilemma":[58],"where":[59],"often":[64],"by":[66,108],"tight":[67],"constraints,":[68],"while":[69],"aggressive":[70],"may":[72],"exacerbate":[73],"performance.":[75],"At":[76],"heart":[78],"this":[80,96],"phenomenon":[81],"are":[82],"diverged":[84],"action":[85],"distribution":[86],"high":[89],"uncertainty":[90,119,133],"value":[93,122,136],"function.":[94],"In":[95],"paper,":[97],"we":[98],"propose":[99],"extend":[101],"datasets":[105],"during":[106],"training":[107],"adding":[109],"gradient-based":[110],"perturbation":[111],"state":[114,156],"utilizing":[116],"estimated":[118,132],"function":[123,137],"constrain":[125],"range":[127,145],"gradient.":[130],"The":[131,158,180],"works":[138],"as":[139],"a":[140],"guidance":[141],"adjust":[143],"automatically,":[148],"ensuring":[149],"adaptability":[151],"reliability":[153],"perturbation.":[157],"proposed":[159],"algorithm":[160],"Uncertainty-Aware":[161],"Augmentation(UADA),":[163],"plugged":[165],"into":[166],"various":[167],"standard":[168],"RL":[170],"algorithms":[171],"evaluated":[173],"on":[174],"several":[175],"rein-forcement":[177],"learning":[178],"tasks.":[179],"empirical":[181],"results":[182],"confirm":[183],"UADA":[185],"substantially":[186],"improves":[187],"performance":[189],"achieves":[191],"better":[192],"model":[193],"stability":[194],"compared":[195],"with":[196],"original":[198],"algorithms.":[199]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
