乐胖代购免代理版

{"id":"https://openalex.org/W4295124924","doi":"https://doi.org/10.48550/arxiv.2209.03880","title":"Learning Sparse Graphon Mean Field Games","display_name":"Learning Sparse Graphon Mean Field Games","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4295124924","doi":"https://doi.org/10.48550/arxiv.2209.03880"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2209.03880","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_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2209.03880","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067265291","display_name":"Christian Fabi\u00e1n","orcid":"https://orcid.org/0000-0003-4239-3861"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fabian, Christian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082267036","display_name":"Kai Cui","orcid":"https://orcid.org/0000-0002-2605-0386"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Kai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070544702","display_name":"Heinz Koeppl","orcid":"https://orcid.org/0000-0002-8305-9379"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Koeppl, Heinz","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"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":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":60},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.8363,"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":0.8363,"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/T11031","display_name":"Game Theory and Applications","score":0.8118,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.7797,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71255285},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.63863015},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.57245505},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.52717936},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.492585},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.48482338},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47525308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4437539},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4050959},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15692979},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2209.03880","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_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2209.03880","pdf_url":"http://arxiv.org/pdf/2209.03880","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2209.03880","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2209.03880","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_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"score":0.82,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4380318855","https://openalex.org/W4362501864","https://openalex.org/W4306904969","https://openalex.org/W3049728571","https://openalex.org/W2964765435","https://openalex.org/W2586732548","https://openalex.org/W2389214306","https://openalex.org/W2138720691","https://openalex.org/W2031695474","https://openalex.org/W2024136090"],"abstract_inverted_index":{"Although":[0],"the":[1,13,34,45,82,139,153,177],"field":[2,30],"of":[3,22,37,48,76,86,141,180,199,203],"multi-agent":[4],"reinforcement":[5],"learning":[6,93,143,158,165,193],"(MARL)":[7],"has":[8],"made":[9],"considerable":[10],"progress":[11],"in":[12,115,206],"last":[14],"years,":[15],"solving":[16],"systems":[17,146],"with":[18,147],"a":[19,25,73,91,173,188,196],"large":[20,197],"number":[21],"agents":[23],"remains":[24],"hard":[26],"challenge.":[27],"Graphon":[28],"mean":[29],"games":[31],"(GMFGs)":[32],"enable":[33],"scalable":[35],"analysis":[36,175],"MARL":[38],"problems":[39,202],"that":[40,137],"are":[41,58,112],"otherwise":[42,200],"intractable.":[43],"By":[44],"mathematical":[46],"structure":[47],"graphons,":[49],"this":[50],"approach":[51,144,194],"is":[52],"limited":[53],"to":[54,60,95,160,163,195],"dense":[55],"graphs":[56],"which":[57,80,111],"insufficient":[59],"describe":[61],"many":[62,148],"real-world":[63],"networks":[64,110],"such":[65],"as":[66],"power":[67,108],"law":[68,109],"graphs.":[69],"Our":[70],"paper":[71],"introduces":[72],"novel":[74,178],"formulation":[75],"GMFGs,":[77],"called":[78],"LPGMFGs,":[79],"leverages":[81],"graph":[83],"theoretical":[84,128,174],"concept":[85,179],"$L^p$":[87],"graphons":[88],"and":[89,97,119,130,133,171],"provides":[90],"machine":[92,192],"tool":[94],"efficiently":[96],"accurately":[98],"approximate":[99],"solutions":[100],"for":[101,145],"sparse":[102],"network":[103],"problems.":[104],"This":[105],"especially":[106],"includes":[107],"empirically":[113,167],"observed":[114],"various":[116],"application":[117],"areas":[118],"cannot":[120],"be":[121],"captured":[122],"by":[123],"standard":[124],"graphons.":[125,183],"We":[126],"derive":[127],"existence":[129],"convergence":[131],"guarantees":[132],"give":[134],"empirical":[135],"examples":[136],"demonstrate":[138],"accuracy":[140],"our":[142,161],"agents.":[149],"Furthermore,":[150],"we":[151,186],"extend":[152],"Online":[154],"Mirror":[155],"Descent":[156],"(OMD)":[157],"algorithm":[159],"setup":[162],"accelerate":[164],"speed,":[166],"show":[168],"its":[169],"capabilities,":[170],"conduct":[172],"using":[176],"smoothed":[181],"step":[182],"In":[184],"general,":[185],"provide":[187],"scalable,":[189],"mathematically":[190],"well-founded":[191],"class":[198],"intractable":[201],"great":[204],"relevance":[205],"numerous":[207],"research":[208],"fields.":[209]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4295124924","counts_by_year":[],"updated_date":"2025-01-21T07:03:39.618185","created_date":"2022-09-11"}