{"id":"https://openalex.org/W7162796788","doi":"https://doi.org/10.48550/arxiv.2605.30190","title":"Mean-Field Diffuser: Scaling Offline MARL to Thousands of Agents","display_name":"Mean-Field Diffuser: Scaling Offline MARL to Thousands of Agents","publication_year":2026,"publication_date":"2026-05-28","ids":{"openalex":"https://openalex.org/W7162796788","doi":"https://doi.org/10.48550/arxiv.2605.30190"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30190","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30190","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":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.2605.30190","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137318700","display_name":"Wenhao Li","orcid":"https://orcid.org/0009-0006-1400-3773"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Wenhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137329962","display_name":"Xiangfeng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiangfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137337481","display_name":"Bo Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Bo","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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6883999705314636,"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":0.6883999705314636,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.0917000025510788,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.03660000115633011,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5782999992370605},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5681999921798706},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.5246999859809875},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.48159998655319214},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.4406999945640564},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.35920000076293945},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.3463999927043915}],"concepts":[{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5782999992370605},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5681999921798706},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5472000241279602},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.5246999859809875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5006999969482422},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3865000009536743},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.3463999927043915},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.30320000648498535},{"id":"https://openalex.org/C169733012","wikidata":"https://www.wikidata.org/wiki/Q1613416","display_name":"Population size","level":3,"score":0.28200000524520874},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.2623000144958496},{"id":"https://openalex.org/C165661538","wikidata":"https://www.wikidata.org/wiki/Q7829327","display_name":"Tournament selection","level":3,"score":0.2605000138282776},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C91873725","wikidata":"https://www.wikidata.org/wiki/Q3445816","display_name":"Function approximation","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30190","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30190","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.30190","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30190","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Diffusion-based":[0],"planning":[1,37],"has":[2],"achieved":[3],"strong":[4],"results":[5],"in":[6,24,157],"single-agent":[7],"offline":[8,108,168],"reinforcement":[9],"learning,":[10],"yet":[11],"scaling":[12],"to":[13,19,38],"many-agent":[14],"systems":[15],"remains":[16],"intractable":[17],"due":[18],"the":[20,25,39,46,58,85,121,154,158,163],"curse":[21],"of":[22,42,48,55,160],"dimensionality":[23],"joint":[26],"trajectory":[27,36,43],"space.":[28],"We":[29,90],"introduce":[30],"MF-Diffuser,":[31],"a":[32,51,65,78],"framework":[33],"that":[34,70,82,100],"lifts":[35],"Wasserstein":[40],"space":[41],"distributions,":[44],"where":[45],"propagation":[47],"chaos":[49],"ensures":[50],"small":[52],"representative":[53],"subset":[54],"agents":[56],"captures":[57],"full":[59],"population":[60,87,116],"dynamics.":[61],"Our":[62],"approach":[63],"features":[64],"value-weighted":[66],"chaotic":[67],"entropy":[68],"objective":[69],"reconciles":[71],"generative":[72],"fidelity":[73],"with":[74,95,115,130,162],"return":[75,156],"maximization,":[76],"and":[77,119,146,170],"hierarchical":[79],"coarse-to-fine":[80],"strategy":[81],"progressively":[83],"grows":[84],"agent":[86],"during":[88],"denoising.":[89],"establish":[91],"end-to-end":[92],"suboptimality":[93],"bounds":[94],"four":[96],"interpretable":[97],"terms,":[98],"revealing":[99],"mean-field":[101,127,137],"approximation":[102],"error":[103],"scales":[104,173],"as":[105],"$O(H^2/\\sqrt{N})$":[106],"while":[107],"distribution":[109],"shift":[110],"provably":[111],"does":[112],"not":[113],"grow":[114],"size":[117],"$N$,":[118],"prove":[120],"generated":[122],"policy":[123],"is":[124],"an":[125],"approximate":[126],"Nash":[128],"equilibrium":[129],"explicit":[131],"convergence":[132],"guarantees.":[133],"Experiments":[134],"on":[135,166],"three":[136],"RL":[138],"benchmarks":[139],"--":[140,150],"spanning":[141],"stage":[142],"games,":[143],"sequential":[144],"dynamics,":[145],"adversarial":[147],"team":[148],"competition":[149],"show":[151],"MF-Diffuser":[152],"achieves":[153],"best":[155],"majority":[159],"settings,":[161],"largest":[164],"gains":[165],"suboptimal":[167],"data":[169],"at":[171],"extreme":[172],"($N":[174],"\\geq":[175],"10^3$).":[176]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-30T00:00:00"}