{"id":"https://openalex.org/W4281661226","doi":"https://doi.org/10.3390/e24060774","title":"Optimal Policy of Multiplayer Poker via Actor-Critic Reinforcement Learning","display_name":"Optimal Policy of Multiplayer Poker via Actor-Critic Reinforcement Learning","publication_year":2022,"publication_date":"2022-05-30","ids":{"openalex":"https://openalex.org/W4281661226","doi":"https://doi.org/10.3390/e24060774","pmid":"https://pubmed.ncbi.nlm.nih.gov/35741495"},"language":"en","primary_location":{"id":"doi:10.3390/e24060774","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24060774","pdf_url":"https://www.mdpi.com/1099-4300/24/6/774/pdf?version=1654481671","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/24/6/774/pdf?version=1654481671","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012434681","display_name":"Daming Shi","orcid":"https://orcid.org/0000-0001-8327-555X"},"institutions":[{"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":true,"raw_author_name":"Daming Shi","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing 100084, China"],"raw_orcid":"https://orcid.org/0000-0001-8327-555X","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053676942","display_name":"Xudong Guo","orcid":"https://orcid.org/0000-0002-9607-2679"},"institutions":[{"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":"Xudong Guo","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing 100084, China"],"raw_orcid":"https://orcid.org/0000-0002-9607-2679","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100330660","display_name":"Yi Liu","orcid":"https://orcid.org/0009-0001-4797-7826"},"institutions":[{"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":"Yi Liu","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing 100084, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100693811","display_name":"Wenhui Fan","orcid":"https://orcid.org/0000-0002-0040-5759"},"institutions":[{"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":"Wenhui Fan","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing 100084, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5012434681"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.5549,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71437616,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"24","issue":"6","first_page":"774","last_page":"774"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9995999932289124,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.9995999932289124,"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/T11705","display_name":"Gambling Behavior and Treatments","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9937000274658203,"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":0.7582736015319824},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.659913182258606},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4422135055065155},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4232112467288971},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.321725070476532}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7582736015319824},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.659913182258606},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4422135055065155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4232112467288971},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.321725070476532}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e24060774","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24060774","pdf_url":"https://www.mdpi.com/1099-4300/24/6/774/pdf?version=1654481671","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:35741495","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35741495","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:e206a1825f4c4d27a3b6101fa2f012e4","is_oa":true,"landing_page_url":"https://doaj.org/article/e206a1825f4c4d27a3b6101fa2f012e4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 24, Iss 6, p 774 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/24/6/774/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e24060774","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 24; Issue 6; Pages: 774","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9222241","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9222241","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e24060774","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24060774","pdf_url":"https://www.mdpi.com/1099-4300/24/6/774/pdf?version=1654481671","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4281661226.pdf","grobid_xml":"https://content.openalex.org/works/W4281661226.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1494895283","https://openalex.org/W1714211023","https://openalex.org/W2006791053","https://openalex.org/W2061499312","https://openalex.org/W2099618002","https://openalex.org/W2145339207","https://openalex.org/W2173564293","https://openalex.org/W2257979135","https://openalex.org/W2574978968","https://openalex.org/W2750605955","https://openalex.org/W2766447205","https://openalex.org/W2768629321","https://openalex.org/W2773381986","https://openalex.org/W2808878233","https://openalex.org/W2892013712","https://openalex.org/W2911296969","https://openalex.org/W2960876848","https://openalex.org/W3112329196","https://openalex.org/W6638018090","https://openalex.org/W6681187623"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4306904969","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2138720691","https://openalex.org/W2376932109"],"abstract_inverted_index":{"Poker":[0],"has":[1,75],"been":[2],"considered":[3],"a":[4,63,123],"challenging":[5],"problem":[6],"in":[7,47],"both":[8],"artificial":[9],"intelligence":[10],"and":[11,21,35,55,109,135,146,186,213,227,236],"game":[12],"theory":[13],"because":[14],"poker":[15,89,126,162,212],"is":[16,39,57,65],"characterized":[17],"by":[18,180],"imperfect":[19,107,201,219,230],"information":[20,108,202,220,226,231],"uncertainty,":[22],"which":[23],"are":[24],"similar":[25],"to":[26,59,103,113,163,217,239],"many":[27],"realistic":[28,77],"problems":[29],"like":[30],"auctioning,":[31],"pricing,":[32],"cyber":[33],"security,":[34],"operations.":[36],"However,":[37],"it":[38,56],"not":[40],"clear":[41],"that":[42],"playing":[43],"an":[44,69,82,234,241],"equilibrium":[45],"policy":[46,64,72,84,127,131,138,171,197],"multi-player":[48,88,125,143,147],"games":[49,90,203],"would":[50],"be":[51,215],"wise":[52],"so":[53],"far,":[54],"infeasible":[58],"theoretically":[60],"validate":[61,164],"whether":[62],"optimal.":[66],"Therefore,":[67],"designing":[68],"effective":[70,235],"optimal":[71,83,170,243],"learning":[73,85,172,198,208,240],"method":[74,86],"more":[76],"significance.":[78],"This":[79],"paper":[80,98,121,153],"proposes":[81,122],"for":[87,142],"based":[91,204],"on":[92,205,211],"Actor-Critic":[93,206],"reinforcement":[94,207],"learning.":[95],"Firstly,":[96],"this":[97,120,152],"builds":[99],"the":[100,110,155,165,168,177,181,191,196],"Actor":[101],"network":[102,112],"make":[104],"decisions":[105],"with":[106,116,190,224,229],"Critic":[111],"evaluate":[114],"policies":[115,178],"perfect":[117,225],"information.":[118],"Secondly,":[119],"novel":[124],"update":[128,132,139],"method:":[129],"asynchronous":[130,137],"algorithm":[133,140],"(APU)":[134],"dual-network":[136],"(Dual-APU)":[141],"multi-policy":[144],"scenarios":[145],"sharing-policy":[148],"scenarios,":[149],"respectively.":[150],"Finally,":[151],"takes":[154],"most":[156],"popular":[157],"six-player":[158],"Texas":[159],"hold":[160],"'em":[161],"performance":[166],"of":[167,200],"proposed":[169,182],"method.":[173],"The":[174],"experiments":[175],"demonstrate":[176],"learned":[179],"methods":[183,199],"perform":[184,209],"well":[185,210],"gain":[187],"steadily":[188],"compared":[189],"existing":[192],"approaches.":[193],"In":[194],"sum,":[195],"can":[214],"transferred":[216],"other":[218],"games.":[221],"Such":[222],"training":[223],"testing":[228],"models":[232],"show":[233],"explainable":[237],"approach":[238],"approximately":[242],"policy.":[244]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}