{"id":"https://openalex.org/W4416578487","doi":"https://doi.org/10.3390/a18120738","title":"Mxplainer: Explain and Learn Insights by Imitating Mahjong Agents","display_name":"Mxplainer: Explain and Learn Insights by Imitating Mahjong Agents","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W4416578487","doi":"https://doi.org/10.3390/a18120738"},"language":"en","primary_location":{"id":"doi:10.3390/a18120738","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18120738","pdf_url":"https://www.mdpi.com/1999-4893/18/12/738/pdf","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"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":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/18/12/738/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100774098","display_name":"Lingfeng Li","orcid":"https://orcid.org/0000-0001-9872-002X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingfeng Li","raw_affiliation_strings":["School of Computer Science, Peking University, Beijing 100871, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036352356","display_name":"Yunlong Lu","orcid":"https://orcid.org/0000-0001-9552-5130"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunlong Lu","raw_affiliation_strings":["School of Computer Science, Peking University, Beijing 100871, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120183237","display_name":"Yongyi Wang","orcid":"https://orcid.org/0000-0003-1111-1294"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongyi Wang","raw_affiliation_strings":["School of Computer Science, Peking University, Beijing 100871, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120048168","display_name":"Qifan Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qifan Zheng","raw_affiliation_strings":["School of Computer Science, Peking University, Beijing 100871, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100397214","display_name":"Wenxin Li","orcid":"https://orcid.org/0000-0003-1744-7792"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenxin Li","raw_affiliation_strings":["School of Computer Science, Peking University, Beijing 100871, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100397214"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19347622,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"12","first_page":"738","last_page":"738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.7955999970436096,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.7955999970436096,"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":0.04430000111460686,"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":0.0210999995470047,"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/randomness","display_name":"Randomness","score":0.7746999859809875},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5996000170707703},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.5489000082015991},{"id":"https://openalex.org/keywords/imperfect","display_name":"Imperfect","score":0.5315999984741211},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5293999910354614},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.34459999203681946}],"concepts":[{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.7746999859809875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7523999810218811},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6484000086784363},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5996000170707703},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5683000087738037},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.5489000082015991},{"id":"https://openalex.org/C2780310539","wikidata":"https://www.wikidata.org/wiki/Q12547192","display_name":"Imperfect","level":2,"score":0.5315999984741211},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5293999910354614},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C123676819","wikidata":"https://www.wikidata.org/wiki/Q1074338","display_name":"Perfect information","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.30649998784065247},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2840999960899353},{"id":"https://openalex.org/C2780154230","wikidata":"https://www.wikidata.org/wiki/Q513420","display_name":"Undo","level":2,"score":0.26249998807907104}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/a18120738","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18120738","pdf_url":"https://www.mdpi.com/1999-4893/18/12/738/pdf","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"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":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5a1e771d22c24df897ceba085b3ceac2","is_oa":true,"landing_page_url":"https://doaj.org/article/5a1e771d22c24df897ceba085b3ceac2","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 18, Iss 12, p 738 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a18120738","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18120738","pdf_url":"https://www.mdpi.com/1999-4893/18/12/738/pdf","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"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":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416578487.pdf"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1999874108","https://openalex.org/W2011835437","https://openalex.org/W2166302491","https://openalex.org/W2257979135","https://openalex.org/W2282821441","https://openalex.org/W2766447205","https://openalex.org/W2773381986","https://openalex.org/W2809129829","https://openalex.org/W2960876848","https://openalex.org/W2982316857","https://openalex.org/W3044916305","https://openalex.org/W3090729135","https://openalex.org/W3116286104","https://openalex.org/W4296474779","https://openalex.org/W4296474781","https://openalex.org/W4367599025","https://openalex.org/W4386193536","https://openalex.org/W4415367908"],"related_works":[],"abstract_inverted_index":{"People":[0],"need":[1],"to":[2,9,52,91,136],"internalize":[3],"the":[4,36,93],"skills":[5],"of":[6,38,54,95,114],"AI":[7,39,44,103],"agents":[8,45,60,104],"improve":[10],"their":[11],"own":[12],"capabilities.":[13],"Our":[14],"paper":[15,75],"focuses":[16],"on":[17,99],"Mahjong,":[18],"a":[19,78,109],"multiplayer":[20],"game":[21],"involving":[22],"imperfect":[23],"information":[24],"and":[25,32,102,117,123,144],"requiring":[26],"effective":[27],"long-term":[28],"decision-making":[29],"amidst":[30],"randomness":[31],"hidden":[33],"information.":[34],"Through":[35],"efforts":[37],"researchers,":[40],"several":[41],"impressive":[42],"Mahjong":[43],"have":[46],"already":[47],"achieved":[48],"performance":[49],"levels":[50],"comparable":[51],"those":[53],"professional":[55],"human":[56,101],"players;":[57],"however,":[58],"these":[59],"are":[61],"often":[62],"treated":[63],"as":[64],"black":[65],"boxes":[66],"from":[67],"which":[68],"few":[69],"insights":[70,140],"can":[71,83],"be":[72,84],"gleaned.":[73],"This":[74,133],"introduces":[76],"Mxplainer,":[77],"parameterized":[79],"search":[80],"algorithm":[81],"that":[82,106,126],"converted":[85],"into":[86,141],"an":[87],"equivalent":[88],"neural":[89],"network":[90],"learn":[92],"parameters":[94],"black-box":[96],"agents.":[97],"Experiments":[98],"both":[100,138],"demonstrate":[105],"Mxplainer":[107,135],"achieves":[108],"top-three":[110,131],"action":[111],"prediction":[112],"accuracy":[113],"over":[115],"92%":[116],"90%,":[118],"respectively,":[119],"while":[120],"providing":[121],"faithful":[122],"interpretable":[124],"approximations":[125],"outperform":[127],"decision-tree":[128],"methods":[129],"(34.8%":[130],"accuracy).":[132],"enables":[134],"deliver":[137],"strategy-level":[139],"agent":[142],"characteristics":[143],"actionable,":[145],"step-by-step":[146],"explanations":[147],"for":[148],"individual":[149],"decisions.":[150]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-25T00:00:00"}
