{"id":"https://openalex.org/W4387559383","doi":"https://doi.org/10.48550/arxiv.2310.04796","title":"Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning","display_name":"Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning","publication_year":2023,"publication_date":"2023-10-07","ids":{"openalex":"https://openalex.org/W4387559383","doi":"https://doi.org/10.48550/arxiv.2310.04796"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2310.04796","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.04796","pdf_url":"https://arxiv.org/pdf/2310.04796","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2310.04796","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100380049","display_name":"Jiayu Chen","orcid":"https://orcid.org/0000-0002-7708-5247"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chen, Jiayu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062497242","display_name":"Zelai Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Zelai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100461870","display_name":"Yunfei Li","orcid":"https://orcid.org/0000-0003-1734-5008"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yunfei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100720881","display_name":"Chao Yu","orcid":"https://orcid.org/0000-0001-7049-6409"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Chao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008049062","display_name":"Jiaming Song","orcid":"https://orcid.org/0000-0002-1931-1699"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Jiaming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023755254","display_name":"Huazhong Yang","orcid":"https://orcid.org/0000-0003-2421-353X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Huazhong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061127138","display_name":"Fei Fang","orcid":"https://orcid.org/0000-0003-2256-8329"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Fei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445144","display_name":"Yu Wang","orcid":"https://orcid.org/0000-0002-0431-1039"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101541675","display_name":"Yi Wu","orcid":"https://orcid.org/0000-0001-6731-1346"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yi","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5100380049"],"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":0.996399998664856,"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":0.996399998664856,"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/T11674","display_name":"Sports Analytics and Performance","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9861000180244446,"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/subgame-perfect-equilibrium","display_name":"Subgame perfect equilibrium","score":0.6851941347122192},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6651982069015503},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6076815724372864},{"id":"https://openalex.org/keywords/curriculum","display_name":"Curriculum","score":0.55012047290802},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34206825494766235},{"id":"https://openalex.org/keywords/nash-equilibrium","display_name":"Nash equilibrium","score":0.2911611497402191},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.27624720335006714},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24252521991729736}],"concepts":[{"id":"https://openalex.org/C175983524","wikidata":"https://www.wikidata.org/wiki/Q1615834","display_name":"Subgame perfect equilibrium","level":3,"score":0.6851941347122192},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6651982069015503},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6076815724372864},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.55012047290802},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34206825494766235},{"id":"https://openalex.org/C46814582","wikidata":"https://www.wikidata.org/wiki/Q23389","display_name":"Nash equilibrium","level":2,"score":0.2911611497402191},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.27624720335006714},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24252521991729736},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2310.04796","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.04796","pdf_url":"https://arxiv.org/pdf/2310.04796","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2310.04796","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2310.04796","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2310.04796","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.04796","pdf_url":"https://arxiv.org/pdf/2310.04796","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4387559383.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W169328966","https://openalex.org/W2390279801","https://openalex.org/W4306904969","https://openalex.org/W2358668433","https://openalex.org/W2138720691","https://openalex.org/W2376932109","https://openalex.org/W4362501864","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Learning":[0,126],"Nash":[1],"equilibrium":[2],"(NE)":[3],"in":[4,150],"complex":[5],"zero-sum":[6,62],"games":[7,42],"with":[8,142,187],"multi-agent":[9],"reinforcement":[10],"learning":[11,19,59,136],"(MARL)":[12],"can":[13,81,139],"be":[14,140],"extremely":[15],"computationally":[16],"expensive.":[17],"Curriculum":[18,125],"is":[20,35,129,192],"an":[21,28,66],"effective":[22],"way":[23],"to":[24,74,84,102,119],"accelerate":[25],"learning,":[26],"but":[27],"under-explored":[29],"dimension":[30],"for":[31,61,112],"generating":[32],"a":[33,47,55,93,108,130],"curriculum":[34,58,135],"the":[36,39,99,133,151,168,183],"difficulty-to-learn":[37],"of":[38,132,185],"subgames":[40],"--":[41],"induced":[43],"by":[44,71],"starting":[45],"from":[46],"specific":[48],"state.":[49],"In":[50,167],"this":[51,89],"work,":[52],"we":[53,91],"present":[54],"novel":[56],"subgame":[57,94,113,134],"framework":[60],"games.":[63],"It":[64],"adopts":[65],"adaptive":[67],"initial":[68],"state":[69,110],"distribution":[70],"resetting":[72],"agents":[73],"some":[75],"previously":[76],"visited":[77],"states":[78],"where":[79],"they":[80],"quickly":[82],"learn":[83],"improve":[85],"performance.":[86],"Building":[87],"upon":[88],"framework,":[90],"derive":[92],"selection":[95],"metric":[96],"that":[97],"approximates":[98],"squared":[100],"distance":[101],"NE":[103],"values":[104],"and":[105,154,179],"further":[106],"adopt":[107],"particle-based":[109],"sampler":[111],"generation.":[114],"Integrating":[115],"these":[116],"techniques":[117],"leads":[118],"our":[120],"new":[121],"algorithm,":[122],"Subgame":[123],"Automatic":[124],"(SACL),":[127],"which":[128],"realization":[131],"framework.":[137],"SACL":[138,160,173],"combined":[141],"any":[143],"MARL":[144],"algorithm":[145],"such":[146],"as":[147],"MAPPO.":[148],"Experiments":[149],"particle-world":[152],"environment":[153,158],"Google":[155],"Research":[156],"Football":[157],"show":[159],"produces":[161,174],"much":[162],"stronger":[163],"policies":[164],"than":[165],"baselines.":[166],"challenging":[169],"hide-and-seek":[170],"quadrant":[171],"environment,":[172],"all":[175],"four":[176],"emergent":[177],"stages":[178],"uses":[180],"only":[181],"half":[182],"samples":[184],"MAPPO":[186],"self-play.":[188],"The":[189],"project":[190],"website":[191],"at":[193],"https://sites.google.com/view/sacl-rl.":[194]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2023-10-12T00:00:00"}
