{"id":"https://openalex.org/W4399800609","doi":"https://doi.org/10.1109/lra.2024.3416789","title":"BeTAIL: Behavior Transformer Adversarial Imitation Learning From Human Racing Gameplay","display_name":"BeTAIL: Behavior Transformer Adversarial Imitation Learning From Human Racing Gameplay","publication_year":2024,"publication_date":"2024-06-19","ids":{"openalex":"https://openalex.org/W4399800609","doi":"https://doi.org/10.1109/lra.2024.3416789"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2024.3416789","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3416789","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","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/A5044517807","display_name":"Catherine Weaver","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Catherine Weaver","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-8521-9305","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101867083","display_name":"Chen Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Tang","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-7536-9983","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102834661","display_name":"Ce Hao","orcid":"https://orcid.org/0009-0000-7653-9713"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ce Hao","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0009-0000-7653-9713","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006805979","display_name":"Kenta Kawamoto","orcid":"https://orcid.org/0000-0001-7276-2766"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kenta Kawamoto","raw_affiliation_strings":["Sony Research, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-7276-2766","affiliations":[{"raw_affiliation_string":"Sony Research, Tokyo, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064077634","display_name":"Masayoshi Tomizuka","orcid":"https://orcid.org/0000-0003-0206-6639"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Masayoshi Tomizuka","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0206-6639","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101770873","display_name":"Wei Zhan","orcid":"https://orcid.org/0000-0002-1474-1200"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Zhan","raw_affiliation_strings":["Department of Mechanical Engineering, University of California, Berkeley, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1474-1200","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of California, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5044517807"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":0.7142,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69824219,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"9","issue":"8","first_page":"7302","last_page":"7309"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9858999848365784,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9768999814987183,"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/transformer","display_name":"Transformer","score":0.6820757389068604},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.655517578125},{"id":"https://openalex.org/keywords/imitation","display_name":"Imitation","score":0.5810793042182922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5315057635307312},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.42695146799087524},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36699819564819336},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.3221674859523773},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.31400537490844727},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23427027463912964},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.2033776044845581},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.15488910675048828}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6820757389068604},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.655517578125},{"id":"https://openalex.org/C126388530","wikidata":"https://www.wikidata.org/wiki/Q1131737","display_name":"Imitation","level":2,"score":0.5810793042182922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5315057635307312},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.42695146799087524},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36699819564819336},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3221674859523773},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.31400537490844727},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23427027463912964},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.2033776044845581},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.15488910675048828},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2024.3416789","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3416789","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W2502115930"],"abstract_inverted_index":{"Autonomous":[0],"racing":[1,176,189],"poses":[2],"a":[3,47,120],"significant":[4],"challenge":[5],"for":[6,152],"control,":[7],"requiring":[8,24],"planning":[9],"minimum-time":[10],"trajectories":[11],"under":[12],"uncertain":[13],"dynamics":[14,56],"and":[15,57,104,150,187,191],"controlling":[16],"vehicles":[17],"at":[18],"their":[19],"handling":[20,105],"limits.":[21],"Current":[22],"methods":[23],"hand-designed":[25],"physical":[26],"models":[27],"or":[28,35,79,155],"reward":[29],"functions":[30],"specific":[31],"to":[32,45,74,76,137,141],"each":[33],"car":[34],"track.":[36],"In":[37,89],"contrast,":[38,90],"imitation":[39],"learning":[40],"uses":[41],"only":[42],"expert":[43],"demonstrations":[44,127,168],"learn":[46],"control":[48],"policy.":[49],"Imitated":[50],"policies":[51],"must":[52],"model":[53,142],"complex":[54,106],"environment":[55,158,185],"human":[58,126,148,171],"decision-making.":[59],"Sequence":[60],"modeling":[61],"is":[62,197],"highly":[63],"effective":[64],"in":[65,85,157,173],"capturing":[66],"intricate":[67],"patterns":[68],"of":[69,147,169],"motion":[70,107],"sequences":[71],"but":[72,99],"struggles":[73,100],"adapt":[75],"new":[77],"environments":[78],"distribution":[80],"shifts":[81,156],"that":[82],"are":[83],"common":[84],"real-world":[86],"robotics":[87],"tasks.":[88],"Adversarial":[91,115],"Imitation":[92,116],"Learning":[93],"(AIL)":[94],"can":[95],"mitigate":[96],"this":[97],"effect,":[98],"with":[101,128,166],"sample":[102],"inefficiency":[103],"patterns.":[108],"Thus,":[109],"we":[110],"propose":[111],"BeTAIL:":[112],"Behavior":[113,121],"Transformer":[114,122],"Learning,":[117],"which":[118],"combines":[119],"(BeT)":[123],"policy":[124,136,140],"from":[125],"online":[129],"AIL.":[130],"BeTAIL":[131,162,183],"adds":[132],"an":[133],"AIL":[134],"residual":[135],"the":[138,143,174,195],"BeT":[139,196],"sequential":[144],"decision-making":[145],"process":[146],"experts":[149],"correct":[151],"out-of-distribution":[153],"states":[154],"dynamics.":[159],"We":[160],"test":[161],"on":[163,199],"three":[164],"challenges":[165],"expert-level":[167],"real":[170],"gameplay":[172],"high-fidelity":[175],"game":[177],"Gran":[178],"Turismo":[179],"Sport.":[180],"Our":[181],"proposed":[182],"reduces":[184],"interactions":[186],"improves":[188],"performance":[190],"stability,":[192],"even":[193],"when":[194],"pretrained":[198],"different":[200],"tracks":[201],"than":[202],"downstream":[203],"learning.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}