{"id":"https://openalex.org/W4416251515","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228126","title":"Pattern Extraction Learning for Cooperative Multi-Agent Reinforcement Learning","display_name":"Pattern Extraction Learning for Cooperative Multi-Agent Reinforcement Learning","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251515","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228126"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228126","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":"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/A5049451354","display_name":"Yifan Zang","orcid":"https://orcid.org/0000-0003-4537-384X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yifan Zang","raw_affiliation_strings":["Institute of Automation,Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation,Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104219889","display_name":"Jinmin He","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinmin He","raw_affiliation_strings":["Institute of Automation,Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation,Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100399817","display_name":"Kai Li","orcid":"https://orcid.org/0000-0001-7767-3754"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Li","raw_affiliation_strings":["Institute of Automation,Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation,Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074341701","display_name":"Jia Xing","orcid":"https://orcid.org/0000-0002-3716-8646"},"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":"Junliang Xing","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112149353","display_name":"Jian Cheng","orcid":"https://orcid.org/0000-0003-1289-2758"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Cheng","raw_affiliation_strings":["Institute of Automation,Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation,Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5049451354"],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1828549,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.5196999907493591,"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":0.5196999907493591,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.04259999841451645,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.03180000185966492,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7727000117301941},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.583299994468689},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.5789999961853027},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.516700029373169},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4634999930858612},{"id":"https://openalex.org/keywords/learning-curve","display_name":"Learning curve","score":0.3188999891281128}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7727000117301941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7699999809265137},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6434999704360962},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.583299994468689},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.5789999961853027},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5246999859809875},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.516700029373169},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4634999930858612},{"id":"https://openalex.org/C34585555","wikidata":"https://www.wikidata.org/wiki/Q1368723","display_name":"Learning curve","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2630000114440918},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.26190000772476196}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228126","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":[{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1641379095","https://openalex.org/W2292533394","https://openalex.org/W2617547828","https://openalex.org/W2747213132","https://openalex.org/W2786572318","https://openalex.org/W2806824292","https://openalex.org/W2915117209","https://openalex.org/W2981038142","https://openalex.org/W2991046523","https://openalex.org/W2997070234","https://openalex.org/W3030840723","https://openalex.org/W3033672499","https://openalex.org/W3156295478","https://openalex.org/W3176265013","https://openalex.org/W4287309212","https://openalex.org/W4396877652"],"related_works":[],"abstract_inverted_index":{"Multi-agent":[0],"reinforcement":[1],"learning":[2],"(MARL)":[3],"has":[4],"demonstrated":[5],"its":[6],"superiority":[7],"in":[8,194,197],"addressing":[9],"complex":[10,198],"decision-making":[11,77],"tasks":[12],"involving":[13],"multiple":[14],"agents.":[15],"However,":[16],"the":[17,34,45,87,93,104,134,142,151,156,184,190],"intricate":[18],"and":[19,72,78,92,110,146,167,176],"dynamic":[20],"interactions":[21,102,163],"among":[22],"agents":[23],"make":[24],"this":[25,131],"problem":[26,35],"exceptionally":[27],"challenging.":[28],"Existing":[29],"MARL":[30],"methods":[31],"often":[32],"simplify":[33],"by":[36],"implicitly":[37],"decomposing":[38],"shared":[39],"rewards":[40],"into":[41],"individual":[42,109],"utilities,":[43],"neglecting":[44],"underlying":[46],"interconnections":[47],"between":[48,103,164],"relevant":[49],"entities.":[50],"To":[51],"overcome":[52],"these":[53],"limitations,":[54],"we":[55],"propose":[56],"a":[57],"novel":[58],"framework":[59],"of":[60,106,155,192],"Multi-Agent":[61],"Pattern":[62,89,95],"Extraction":[63],"(MAPE),":[64],"which":[65],"captures":[66],"cooperation":[67,175],"patterns":[68],"from":[69,108],"both":[70],"agent-level":[71],"global":[73,111],"perspectives":[74],"to":[75,123,133,149],"enhance":[76],"collaboration":[79],"efficiency.":[80],"Specifically,":[81],"MAPE":[82,171,193],"introduces":[83],"two":[84],"key":[85],"modules:":[86],"Agent":[88],"Extractor":[90,96],"(APE)":[91],"Global":[94],"(GPE)":[97],"that":[98],"focus":[99],"on":[100,118,183],"specific":[101],"entities":[105,125,166],"interests":[107],"perspectives,":[112],"respectively.":[113],"The":[114,137],"APE":[115],"module":[116,139],"focuses":[117],"computing":[119],"each":[120],"agent\u2019s":[121],"attention":[122],"other":[124],"across":[126],"different":[127],"interaction":[128,153],"patterns,":[129],"providing":[130],"information":[132,145],"GPE":[135,138],"module.":[136],"then":[140],"integrates":[141],"agent-specific":[143],"pattern":[144,154],"state":[147],"features":[148],"identify":[150],"overall":[152],"multi-agent":[157,199],"system.":[158],"By":[159],"filtering":[160],"out":[161],"irrelevant":[162],"unrelated":[165],"highlighting":[168],"meaningful":[169],"relationships,":[170],"fosters":[172],"more":[173,178],"focused":[174],"facilitates":[177],"efficient":[179],"learning.":[180],"Extensive":[181],"experiments":[182],"StarCraft":[185],"II":[186],"micromanagement":[187],"benchmark":[188],"showcase":[189],"effectiveness":[191],"improving":[195],"efficiency":[196],"environments.":[200]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-14T00:00:00"}