{"id":"https://openalex.org/W7140933637","doi":"https://doi.org/10.48550/arxiv.2603.23875","title":"Self-Evolving Multi-Agent Framework for Efficient Decision Making in Real-Time Strategy Scenarios","display_name":"Self-Evolving Multi-Agent Framework for Efficient Decision Making in Real-Time Strategy Scenarios","publication_year":2026,"publication_date":"2026-03-25","ids":{"openalex":"https://openalex.org/W7140933637","doi":"https://doi.org/10.48550/arxiv.2603.23875"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.23875","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23875","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.23875","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130682784","display_name":"Li Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130636929","display_name":"Hao Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130707123","display_name":"Yiming Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yiming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130664247","display_name":"Hongbin Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Hongbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130637240","display_name":"Jie Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017039706","display_name":"Kongjing Gu","orcid":"https://orcid.org/0000-0002-1461-6004"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Kongjing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129212786","display_name":"Guanlin Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Guanlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130657912","display_name":"Hui Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Hui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130653113","display_name":"Lei Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.388700008392334,"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":0.388700008392334,"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":0.2773999869823456,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.08889999985694885,"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/inference","display_name":"Inference","score":0.6191999912261963},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5695000290870667},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.460999995470047},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.45329999923706055},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4189999997615814},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.35749998688697815},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.3441999852657318},{"id":"https://openalex.org/keywords/expansive","display_name":"Expansive","score":0.33149999380111694}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7598000168800354},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6191999912261963},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5695000290870667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48969998955726624},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.460999995470047},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.45329999923706055},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4189999997615814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36959999799728394},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.35749998688697815},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C2780502288","wikidata":"https://www.wikidata.org/wiki/Q28838156","display_name":"Expansive","level":3,"score":0.33149999380111694},{"id":"https://openalex.org/C59594135","wikidata":"https://www.wikidata.org/wiki/Q5249242","display_name":"Decision model","level":2,"score":0.323199987411499},{"id":"https://openalex.org/C159254197","wikidata":"https://www.wikidata.org/wiki/Q1144915","display_name":"Lexicographical order","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C115988155","wikidata":"https://www.wikidata.org/wiki/Q3262192","display_name":"Decision problem","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27619999647140503},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C20837028","wikidata":"https://www.wikidata.org/wiki/Q623966","display_name":"Influence diagram","level":3,"score":0.2671999931335449},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.23875","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23875","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.23875","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.23875","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7237327098846436}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4],"demonstrated":[5],"exceptional":[6],"potential":[7],"in":[8,19,23,70,169],"complex":[9,170],"reasoning,pioneering":[10],"a":[11,31,62,123],"new":[12],"paradigm":[13],"for":[14,66],"autonomous":[15],"agent":[16],"decision":[17,141,159],"making":[18],"dynamic":[20,93],"settings.":[21],"However,":[22],"Real-Time":[24],"Strategy":[25],"(RTS)":[26],"scenarios,":[27],"LLMs":[28],"suffer":[29],"from":[30],"critical":[32],"speed-quality":[33],"trade-off.":[34],"Specifically":[35],"expansive":[36],"state":[37],"spaces":[38],"and":[39,87,131,140,167],"time":[40],"limits":[41],"render":[42],"inference":[43,118],"delays":[44],"prohibitive,":[45],"while":[46,156],"stochastic":[47],"planning":[48],"errors":[49],"undermine":[50],"logical":[51],"consistency.":[52,142],"To":[53],"address":[54],"these":[55],"challenges,":[56],"we":[57],"present":[58],"SEMA":[59,151],"(Self-Evolving":[60],"Multi-Agent),":[61],"novel":[63],"framework":[64,76],"designed":[65],"high-performance,":[67],"low-latency":[68],"decision-making":[69],"RTS":[71,171],"environments.":[72],"This":[73],"collaborative":[74],"multi-agent":[75],"facilitates":[77],"self-evolution":[78],"by":[79,161],"adaptively":[80],"calibrating":[81],"model":[82,101],"bias":[83],"through":[84],"in-episode":[85],"assessment":[86],"cross-episode":[88],"analysis.":[89],"We":[90,120],"further":[91],"incorporate":[92],"observation":[94],"pruning":[95],"based":[96],"on":[97],"structural":[98],"entropy":[99],"to":[100],"game":[102],"states":[103],"topologically.":[104],"By":[105],"distilling":[106],"high":[107],"dimensional":[108],"data":[109],"into":[110],"core":[111],"semantic":[112],"information,":[113],"this":[114],"approach":[115],"significantly":[116],"reduces":[117],"time.":[119],"also":[121],"develop":[122],"hybrid":[124],"knowledge-memory":[125],"mechanism":[126],"that":[127,150],"integrates":[128],"micro-trajectories,":[129],"macro-experience,":[130],"hierarchical":[132],"domain":[133],"knowledge,":[134],"thereby":[135],"enhancing":[136],"both":[137],"strategic":[138],"adaptability":[139],"Experiments":[143],"across":[144],"multiple":[145],"StarCraft":[146],"II":[147],"maps":[148],"demonstrate":[149],"achieves":[152],"superior":[153],"win":[154],"rates":[155],"reducing":[157],"average":[158],"latency":[160],"over":[162],"50%,":[163],"validating":[164],"its":[165],"efficiency":[166],"robustness":[168],"scenarios.":[172]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-27T00:00:00"}