{"id":"https://openalex.org/W7128523563","doi":"https://doi.org/10.48550/arxiv.2602.08847","title":"Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems","display_name":"Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems","publication_year":2026,"publication_date":"2026-02-09","ids":{"openalex":"https://openalex.org/W7128523563","doi":"https://doi.org/10.48550/arxiv.2602.08847"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.08847","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100777234","display_name":"Lang Feng","orcid":"https://orcid.org/0000-0003-2543-1344"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Lang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125247902","display_name":"Longtao Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Longtao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125525866","display_name":"Shuo He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Shuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102924801","display_name":"Fuxiang Zhang","orcid":"https://orcid.org/0009-0001-7251-4372"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Fuxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125477636","display_name":"Bo An","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"An, Bo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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":0.6782000064849854,"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":0.6782000064849854,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.06239999830722809,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.012799999676644802,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8058000206947327},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5982000231742859},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.45730000734329224},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4180000126361847},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.38429999351501465},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.302700012922287}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8058000206947327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7182999849319458},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5982000231742859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5475999712944031},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4101000130176544},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.38429999351501465},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.08847","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.08847","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08847","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":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.08847","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-agent":[0],"LLM":[1,41,83,126,133,143],"systems":[2,20],"enable":[3],"advanced":[4],"reasoning":[5,153],"and":[6,76,105,111,135,138,154,160,175,180,183],"tool":[7],"use":[8],"via":[9],"role":[10],"specialization,":[11],"yet":[12],"reliable":[13],"reinforcement":[14],"learning":[15],"(RL)":[16],"post-training":[17],"for":[18,32,81,124],"such":[19],"remains":[21,195],"difficult.":[22],"In":[23],"this":[24,68],"work,":[25],"we":[26,70],"theoretically":[27,110],"pinpoint":[28],"a":[29,49,74],"key":[30],"reason":[31],"training":[33,79,122],"instability":[34],"when":[35],"extending":[36],"group-based":[37],"RL":[38,78,121],"to":[39,63],"multi-agent":[40,82,125,151],"systems.":[42,84],"We":[43,146],"show":[44],"that":[45],"under":[46,198],"GRPO-style":[47],"optimization,":[48],"global":[50],"normalization":[51],"baseline":[52],"may":[53],"deviate":[54],"from":[55],"diverse":[56],"agents'":[57],"reward":[58,99],"distributions,":[59],"which":[60,101],"ultimately":[61],"leads":[62],"gradient-norm":[64],"instability.":[65],"Based":[66],"on":[67,150,178,186],"finding,":[69],"propose":[71],"Dr.":[72,85,116,148,164],"MAS,":[73],"simple":[75],"stable":[77],"recipe":[80],"MAS":[86,117,149,165],"uses":[87],"an":[88,119],"agent-wise":[89],"remedy:":[90],"normalizing":[91],"advantages":[92],"per":[93],"agent":[94],"using":[95,158],"each":[96],"agent's":[97],"own":[98],"statistics,":[100],"calibrates":[102],"gradient":[103,191],"scales":[104],"dramatically":[106],"stabilizes":[107],"training,":[108],"both":[109],"empirically.":[112],"Beyond":[113],"the":[114],"algorithm,":[115],"provides":[118],"end-to-end":[120],"framework":[123],"systems,":[127],"supporting":[128],"scalable":[129],"orchestration,":[130],"flexible":[131],"per-agent":[132],"serving":[134],"optimization":[136],"configs,":[137],"shared":[139],"resource":[140],"scheduling":[141],"of":[142],"actor":[144],"backends.":[145],"evaluate":[147],"math":[152],"multi-turn":[155],"search":[156],"benchmarks":[157],"Qwen2.5":[159],"Qwen3":[161],"series":[162],"models.":[163],"achieves":[166],"clear":[167],"gains":[168],"over":[169],"vanilla":[170],"GRPO":[171],"(e.g.,":[172],"+5.6\\%":[173],"avg@16":[174,182],"+4.6\\%":[176],"pass@16":[177,185],"math,":[179],"+15.2\\%":[181],"+13.1\\%":[184],"search)":[187],"while":[188,202],"largely":[189],"eliminating":[190],"spikes.":[192],"Moreover,":[193],"it":[194],"highly":[196],"effective":[197],"heterogeneous":[199],"agent-model":[200],"assignments":[201],"improving":[203],"efficiency.":[204]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-11T00:00:00"}
