{"id":"https://openalex.org/W7161145948","doi":"https://doi.org/10.48550/arxiv.2605.13269","title":"Submodular Multi-Agent Policy Learning for Online Distributed Task Allocation in Open Multi-Agent Systems","display_name":"Submodular Multi-Agent Policy Learning for Online Distributed Task Allocation in Open Multi-Agent Systems","publication_year":2026,"publication_date":"2026-05-13","ids":{"openalex":"https://openalex.org/W7161145948","doi":"https://doi.org/10.48550/arxiv.2605.13269"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.13269","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.13269","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.13269","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136133682","display_name":"Jing Liu","orcid":"https://orcid.org/0000-0002-6834-5350"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Jing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136158717","display_name":"Yangyang Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Yangyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043137857","display_name":"Luca Ballotta","orcid":"https://orcid.org/0000-0002-6521-7142"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ballotta, Luca","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136147889","display_name":"Fangfei Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Fangfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136093181","display_name":"Yang Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5089846134","display_name":"Ruggero Carli","orcid":"https://orcid.org/0000-0002-6506-5898"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carli, Ruggero","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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":0.8072999715805054,"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":0.8072999715805054,"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/T12794","display_name":"Adaptive Dynamic Programming Control","score":0.04839999973773956,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.024000000208616257,"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":[{"id":"https://openalex.org/keywords/submodular-set-function","display_name":"Submodular set function","score":0.7784000039100647},{"id":"https://openalex.org/keywords/multilinear-map","display_name":"Multilinear map","score":0.4921000003814697},{"id":"https://openalex.org/keywords/common-value-auction","display_name":"Common value auction","score":0.4675999879837036},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.45669999718666077},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.43050000071525574},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.40139999985694885},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.39910000562667847},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.3727000057697296},{"id":"https://openalex.org/keywords/queue","display_name":"Queue","score":0.34540000557899475}],"concepts":[{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.7784000039100647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5428000092506409},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5389000177383423},{"id":"https://openalex.org/C84392682","wikidata":"https://www.wikidata.org/wiki/Q1952404","display_name":"Multilinear map","level":2,"score":0.4921000003814697},{"id":"https://openalex.org/C163239763","wikidata":"https://www.wikidata.org/wiki/Q5153637","display_name":"Common value auction","level":2,"score":0.4675999879837036},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.45669999718666077},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.43050000071525574},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.40139999985694885},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.39910000562667847},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.38440001010894775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38420000672340393},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.3727000057697296},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.33250001072883606},{"id":"https://openalex.org/C106286213","wikidata":"https://www.wikidata.org/wiki/Q898572","display_name":"Matroid","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C2834757","wikidata":"https://www.wikidata.org/wiki/Q4925424","display_name":"Monotone polygon","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.3082999885082245},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3073999881744385},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C152361515","wikidata":"https://www.wikidata.org/wiki/Q181328","display_name":"Bernoulli's principle","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C8505890","wikidata":"https://www.wikidata.org/wiki/Q605095","display_name":"Budget constraint","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C196921405","wikidata":"https://www.wikidata.org/wiki/Q786431","display_name":"Online algorithm","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.13269","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.13269","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":"doi:10.48550/arxiv.2605.13269","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.13269","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":"article"},"sustainable_development_goals":[{"score":0.42146065831184387,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"multi-agent":[3],"reinforcement":[4],"learning":[5],"with":[6,113,158,166,190],"submodular":[7,86,118],"team":[8,77],"utilities":[9],"for":[10],"online":[11],"distributed":[12],"task":[13],"allocation.":[14],"In":[15],"this":[16,60,103],"setting,":[17],"each":[18],"agent":[19],"selects":[20],"one":[21],"action":[22],"from":[23],"a":[24,33,69,96,108,132],"local":[25,182],"categorical":[26,52,81,115],"policy,":[27],"so":[28],"feasible":[29],"joint":[30],"actions":[31],"form":[32],"partition":[34],"matroid":[35],"over":[36],"agent-action":[37],"pairs.":[38],"Classical":[39],"multilinear":[40],"extensions":[41],"use":[42],"independent":[43],"Bernoulli":[44],"sampling":[45],"and":[46,94,117,136,161,175,184,187],"therefore":[47],"do":[48],"not":[49],"match":[50],"the":[51,64,75,123,146,150],"policies":[53,116],"executed":[54],"by":[55,145],"decentralized":[56],"agents.":[57],"To":[58,154],"address":[59],"mismatch,":[61],"we":[62,105,130,163],"introduce":[63],"Partition":[65],"Multilinear":[66],"Extension":[67],"(PME),":[68],"continuous":[70],"relaxation":[71],"whose":[72],"value":[73],"equals":[74],"expected":[76],"utility":[78],"under":[79],"factorized":[80],"policies.":[82,170],"We":[83],"prove":[84,131],"that":[85,179],"difference":[87],"rewards":[88],"provide":[89],"unbiased":[90],"PME":[91,125,152],"marginal-gradient":[92],"information":[93],"yield":[95],"stagewise":[97,133],"score-function":[98],"policy-gradient":[99,111],"estimator.":[100],"Based":[101],"on":[102,172],"connection,":[104],"propose":[106],"SubMAPG,":[107],"centralized-training":[109],"decentralized-execution":[110],"framework":[112],"masked":[114],"difference-reward":[119],"training":[120],"signals.":[121],"For":[122],"associated":[124],"marginal-space":[126],"projected":[127],"stochastic-gradient":[128],"dynamics,":[129],"1/2-approximation":[134],"guarantee":[135],"sublinear":[137],"dynamic":[138],"regret":[139],"in":[140],"slowly":[141],"varying":[142],"environments,":[143],"measured":[144],"path":[147],"length":[148],"of":[149],"optimal":[151],"marginals.":[153],"handle":[155],"open":[156],"systems":[157],"time-varying":[159],"agents":[160],"targets,":[162],"instantiate":[164],"SubMAPG":[165,180],"graph":[167],"neural":[168],"network":[169],"Experiments":[171],"multi-robot":[173],"coverage":[174],"multi-target":[176],"tracking":[177],"show":[178],"outperforms":[181],"greedy":[183,193],"shared-reward":[185],"baselines":[186],"is":[188],"competitive":[189],"centralized":[191],"myopic":[192],"strategies.":[194]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-15T00:00:00"}