{"id":"https://openalex.org/W3109403864","doi":"https://doi.org/10.1109/tg.2022.3158649","title":"Model-Free Neural Counterfactual Regret Minimization With Bootstrap Learning","display_name":"Model-Free Neural Counterfactual Regret Minimization With Bootstrap Learning","publication_year":2022,"publication_date":"2022-03-11","ids":{"openalex":"https://openalex.org/W3109403864","doi":"https://doi.org/10.1109/tg.2022.3158649","mag":"3109403864"},"language":"en","primary_location":{"id":"doi:10.1109/tg.2022.3158649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tg.2022.3158649","pdf_url":null,"source":{"id":"https://openalex.org/S4210224842","display_name":"IEEE Transactions on Games","issn_l":"2475-1502","issn":["2475-1502","2475-1510"],"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 Games","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2012.01870","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100636233","display_name":"Weiming Liu","orcid":"https://orcid.org/0000-0002-4262-639X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiming Liu","raw_affiliation_strings":["School of Data Science, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-4262-639X","affiliations":[{"raw_affiliation_string":"School of Data Science, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365157","display_name":"Bin Li","orcid":"https://orcid.org/0000-0002-2332-3959"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Li","raw_affiliation_strings":["School of Information Science and Technology, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-2332-3959","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077267552","display_name":"Julian Togelius","orcid":"https://orcid.org/0000-0003-3128-4598"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Julian Togelius","raw_affiliation_strings":["Department of Computer Science and Engineering, New York University, New York, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-3128-4598","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, New York University, New York, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7873,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.75159349,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"15","issue":"3","first_page":"315","last_page":"325"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.996399998664856,"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":0.996399998664856,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.9948999881744385,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9915000200271606,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.849399209022522},{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.6870684623718262},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6636791825294495},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.615066647529602},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4754371643066406},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4225672483444214},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35756468772888184},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3345488905906677},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3036718964576721},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27004462480545044},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07607907056808472}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.849399209022522},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.6870684623718262},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6636791825294495},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.615066647529602},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4754371643066406},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4225672483444214},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35756468772888184},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3345488905906677},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3036718964576721},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27004462480545044},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07607907056808472},{"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tg.2022.3158649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tg.2022.3158649","pdf_url":null,"source":{"id":"https://openalex.org/S4210224842","display_name":"IEEE Transactions on Games","issn_l":"2475-1502","issn":["2475-1502","2475-1510"],"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 Games","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2012.01870","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.01870","pdf_url":"https://arxiv.org/pdf/2012.01870","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2012.01870","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.01870","pdf_url":"https://arxiv.org/pdf/2012.01870","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G2262853887","display_name":null,"funder_award_id":"61836011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4198966207","display_name":null,"funder_award_id":"U19B2044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":76,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W41554520","https://openalex.org/W1513468570","https://openalex.org/W1525285119","https://openalex.org/W1543121739","https://openalex.org/W1714211023","https://openalex.org/W1726776292","https://openalex.org/W1980392196","https://openalex.org/W2103315867","https://openalex.org/W2106975967","https://openalex.org/W2113228754","https://openalex.org/W2114793692","https://openalex.org/W2115916905","https://openalex.org/W2121513215","https://openalex.org/W2121863487","https://openalex.org/W2131600418","https://openalex.org/W2144274908","https://openalex.org/W2145339207","https://openalex.org/W2155968351","https://openalex.org/W2165131254","https://openalex.org/W2168356773","https://openalex.org/W2212088069","https://openalex.org/W2294747104","https://openalex.org/W2562576832","https://openalex.org/W2574978968","https://openalex.org/W2605179600","https://openalex.org/W2766447205","https://openalex.org/W2766768413","https://openalex.org/W2773381986","https://openalex.org/W2787894218","https://openalex.org/W2892013712","https://openalex.org/W2899115826","https://openalex.org/W2906281181","https://openalex.org/W2912660065","https://openalex.org/W2922444559","https://openalex.org/W2960876848","https://openalex.org/W2962713264","https://openalex.org/W2963477884","https://openalex.org/W2964019952","https://openalex.org/W2964121744","https://openalex.org/W2964164283","https://openalex.org/W2964381205","https://openalex.org/W2964547635","https://openalex.org/W2964934024","https://openalex.org/W2969287672","https://openalex.org/W3036927735","https://openalex.org/W3080474688","https://openalex.org/W3174079223","https://openalex.org/W4285364563","https://openalex.org/W4285719527","https://openalex.org/W4288626409","https://openalex.org/W4295237430","https://openalex.org/W4297789398","https://openalex.org/W4300920027","https://openalex.org/W6628288438","https://openalex.org/W6630506423","https://openalex.org/W6631190155","https://openalex.org/W6631396142","https://openalex.org/W6675509861","https://openalex.org/W6675551245","https://openalex.org/W6676175064","https://openalex.org/W6678052826","https://openalex.org/W6681187623","https://openalex.org/W6696772115","https://openalex.org/W6737726454","https://openalex.org/W6751671785","https://openalex.org/W6754803952","https://openalex.org/W6755466161","https://openalex.org/W6755963907","https://openalex.org/W6757961460","https://openalex.org/W6758650442","https://openalex.org/W6765807335","https://openalex.org/W6766522991","https://openalex.org/W6766749119","https://openalex.org/W6780162350","https://openalex.org/W6782761583"],"related_works":["https://openalex.org/W2971351794","https://openalex.org/W2132624896","https://openalex.org/W1983202944","https://openalex.org/W2802467175","https://openalex.org/W2022564137","https://openalex.org/W2035984254","https://openalex.org/W4252044174","https://openalex.org/W2118206667","https://openalex.org/W4291127980","https://openalex.org/W633344313"],"abstract_inverted_index":{"Counterfactual":[0],"regret":[1],"minimization":[2],"(CFR)":[3],"has":[4,137],"achieved":[5],"many":[6],"fascinating":[7],"results":[8,147],"in":[9,56],"solving":[10],"large-scale":[11,58],"imperfect":[12],"information":[13,38],"games":[14],"(IIGs).":[15],"Neural":[16],"network":[17],"approximation":[18,55],"CFR":[19,44,70,73,118,158],"(neural":[20],"CFR)":[21],"is":[22,60,75,92,124,152],"one":[23],"of":[24,105,133],"the":[25,128,155],"promising":[26],"techniques":[27],"that":[28,94,149],"can":[29,96],"reduce":[30],"computation":[31],"and":[32,53,85,130],"memory":[33],"consumption":[34],"by":[35],"generalizing":[36],"decision":[37],"between":[39],"similar":[40],"states.":[41],"Current":[42],"neural":[43,117,122,135,144,150,157],"algorithms":[45,159],"have":[46],"to":[47,87,98,127],"approximate":[48],"cumulative":[49,89],"regrets.":[50,90],"However,":[51],"efficient":[52],"accurate":[54],"a":[57,62,68,99,103,114,161],"IIG":[59],"still":[61],"tough":[63],"challenge.":[64],"In":[65,77],"this":[66],"article,":[67],"new":[69,115],"variant,":[71],"recursive":[72,79,129],"(ReCFR),":[74],"proposed.":[76,125],"ReCFR,":[78,113],"substitute":[80],"values":[81],"(RSVs)":[82],"are":[83],"learned":[84],"used":[86],"replace":[88],"It":[91],"proven":[93],"ReCFR":[95],"converge":[97],"Nash":[100],"equilibrium":[101],"at":[102,160],"rate":[104],"<inline-formula":[106],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[107],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[108],"notation=\"LaTeX\">$O({1}/{\\sqrt{T}})$</tex-math></inline-formula>":[109],".":[110],"Based":[111],"on":[112],"model-free":[116],"with":[119,154],"bootstrap":[120],"learning,":[121],"ReCFR-B,":[123],"Due":[126],"noncumulative":[131],"nature":[132],"RSVs,":[134],"ReCFR-B":[136,151],"lower":[138,163],"variance":[139],"training":[140,164],"targets":[141],"than":[142],"other":[143],"CFRs.":[145],"Experimental":[146],"show":[148],"competitive":[153],"state-of-the-art":[156],"much":[162],"cost.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}