{"id":"https://openalex.org/W4416251528","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228626","title":"SPDou: Mastering the DouDiZhu Game with ISPPO Models","display_name":"SPDou: Mastering the DouDiZhu Game with ISPPO Models","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251528","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228626"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228626","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228626","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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/A5101824699","display_name":"Shipeng Wang","orcid":"https://orcid.org/0000-0002-2025-1013"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shipeng Wang","raw_affiliation_strings":["Shenyang Aerospace University,School of Computing,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computing,Shenyang,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455413","display_name":"Yajie Wang","orcid":"https://orcid.org/0000-0002-0962-4464"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yajie Wang","raw_affiliation_strings":["Shenyang Aerospace University,School of Computing,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computing,Shenyang,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038792040","display_name":"Qilong Guo","orcid":"https://orcid.org/0000-0003-3357-5970"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qilong Guo","raw_affiliation_strings":["Shenyang Aerospace University,School of Computing,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computing,Shenyang,China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048297544","display_name":"Tianyu Zhao","orcid":"https://orcid.org/0000-0003-2401-4098"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyu Zhao","raw_affiliation_strings":["Shenyang Aerospace University,School of Computing,Shenyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenyang Aerospace University,School of Computing,Shenyang,China","institution_ids":["https://openalex.org/I125904092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125904092"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32449886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.8348000049591064,"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":0.8348000049591064,"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":0.08590000122785568,"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/T11197","display_name":"Digital Games and Media","score":0.007699999958276749,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/imperfect","display_name":"Imperfect","score":0.5364999771118164},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5339000225067139},{"id":"https://openalex.org/keywords/perfect-information","display_name":"Perfect information","score":0.5080999732017517},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4569000005722046},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4564000070095062},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4138999879360199},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.38760000467300415},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3635999858379364}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7148000001907349},{"id":"https://openalex.org/C2780310539","wikidata":"https://www.wikidata.org/wiki/Q12547192","display_name":"Imperfect","level":2,"score":0.5364999771118164},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5339000225067139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5228999853134155},{"id":"https://openalex.org/C123676819","wikidata":"https://www.wikidata.org/wiki/Q1074338","display_name":"Perfect information","level":2,"score":0.5080999732017517},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.462799996137619},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4569000005722046},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4564000070095062},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.38760000467300415},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3635999858379364},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C73602740","wikidata":"https://www.wikidata.org/wiki/Q7795822","display_name":"Thompson sampling","level":3,"score":0.25429999828338623},{"id":"https://openalex.org/C113336015","wikidata":"https://www.wikidata.org/wiki/Q574010","display_name":"Complete information","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C2777742833","wikidata":"https://www.wikidata.org/wiki/Q1964083","display_name":"Reciprocal","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228626","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228626","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 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":23,"referenced_works":["https://openalex.org/W2209913494","https://openalex.org/W2514260088","https://openalex.org/W2766447205","https://openalex.org/W2951360122","https://openalex.org/W2965394063","https://openalex.org/W2982316857","https://openalex.org/W2996896271","https://openalex.org/W3005709158","https://openalex.org/W3009744918","https://openalex.org/W3093476339","https://openalex.org/W3094503105","https://openalex.org/W3094607870","https://openalex.org/W3118868204","https://openalex.org/W3188220908","https://openalex.org/W3192699428","https://openalex.org/W4283815845","https://openalex.org/W4309347892","https://openalex.org/W4310705874","https://openalex.org/W4312279581","https://openalex.org/W4385819655","https://openalex.org/W4391991946","https://openalex.org/W4396983159","https://openalex.org/W4400111614"],"related_works":[],"abstract_inverted_index":{"DouDiZhu,":[0],"as":[1,73],"an":[2,31,53,169],"imperfect":[3,16,68],"information":[4,75,131],"game,":[5],"poses":[6],"a":[7,117,122,140],"great":[8],"challenge":[9],"to":[10,63,102,110,128],"existing":[11],"technologies":[12],"because":[13],"of":[14,67,83,106,137,143,173,192],"its":[15],"information,":[17,69],"large":[18],"action":[19],"space":[20],"and":[21,76,93,134,156,195],"complex":[22],"situation.":[23],"To":[24],"address":[25],"these":[26],"challenges,":[27],"we":[28,70],"present":[29],"SPDou,":[30],"AI":[32],"system":[33],"specifically":[34],"designed":[35,101],"for":[36,96],"DouDiZhu.":[37],"The":[38],"strategy":[39],"learning":[40],"process":[41],"is":[42,100,147,197],"enhanced":[43],"by":[44],"combining":[45],"empirical":[46],"strategies":[47,51],"with":[48,177],"model":[49],"generation":[50],"using":[52],"Improved":[54],"Sampling":[55],"Proximal":[56],"Policy":[57],"Optimization":[58],"(ISPPO)":[59],"algorithm.":[60],"In":[61,85,126],"order":[62,127],"solve":[64],"the":[65,80,104,111,130,138,162,187,206],"problem":[66],"treat":[71],"it":[72,78,196],"observable":[74],"feed":[77],"into":[79],"critic":[81],"network":[82],"ISPPO.":[84],"addition,":[86],"Reward":[87],"Shaping":[88],"Based":[89],"on":[90],"Hand":[91,98,151],"Scoring":[92],"Difference":[94],"Steps":[95],"Clearing":[97],"Mechanism(RSHSDSM)":[99],"adapt":[103],"value":[105],"our":[107],"hands":[108],"according":[109],"opponent\u2019s":[112],"role":[113],"adaptation,":[114],"which":[115],"provides":[116],"reasonable":[118],"feedback":[119],"mechanism":[120],"in":[121,165,175,180,190],"sparse":[123],"reward":[124],"environment.":[125],"improve":[129],"extraction":[132],"ability":[133],"training":[135],"efficiency":[136],"network,":[139],"new":[141],"method":[142],"game":[144],"state":[145],"encoding":[146],"proposed,":[148],"including":[149],"Card":[150],"Coding,":[152],"Legal":[153],"Combination":[154],"Coding":[155],"Size":[157],"Coding.":[158],"Experiments":[159],"show":[160],"that":[161],"SPDou":[163,183,210],"proposed":[164],"this":[166],"paper":[167],"achieved":[168],"average":[170],"winning":[171],"rate":[172],"65%":[174],"competing":[176],"other":[178,202,217],"agents":[179],"various":[181],"situations.":[182],"performs":[184],"better":[185],"than":[186,201,216],"benchmark":[188],"algorithms":[189],"terms":[191],"decision-making":[193],"speed":[194],"about":[198],"75%":[199],"faster":[200],"agents.":[203,218],"Moreover,":[204],"through":[205],"Elo":[207,214],"rating":[208],"comparison,":[209],"obtained":[211],"significantly":[212],"higher":[213],"scores":[215]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-11-14T00:00:00"}
