{"id":"https://openalex.org/W4416377607","doi":"https://doi.org/10.4230/lipics.forc.2026.14","title":"Fair Multi-Agent Persuasion with Submodular Constraints","display_name":"Fair Multi-Agent Persuasion with Submodular Constraints","publication_year":2025,"publication_date":"2025-11-11","ids":{"openalex":"https://openalex.org/W4416377607","doi":"https://doi.org/10.4230/lipics.forc.2026.14"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2511.08538","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.08538","pdf_url":"https://arxiv.org/pdf/2511.08538","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"article","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2511.08538","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100630904","display_name":"Yang Bai","orcid":"https://orcid.org/0000-0002-6754-6281"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bai, Yannan","raw_affiliation_strings":["Duke University, Durham, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University, Durham, NC, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047351951","display_name":"Kamesh Munagala","orcid":"https://orcid.org/0000-0003-2636-9650"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Munagala, Kamesh","raw_affiliation_strings":["Duke University, Durham, NC, USA"],"raw_orcid":"https://orcid.org/0000-0003-2636-9650","affiliations":[{"raw_affiliation_string":"Duke University, Durham, NC, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102854022","display_name":"Yiheng Shen","orcid":"https://orcid.org/0009-0009-6719-8959"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Yiheng","raw_affiliation_strings":["Duke University, Durham, NC, USA"],"raw_orcid":"https://orcid.org/0009-0009-6719-8959","affiliations":[{"raw_affiliation_string":"Duke University, Durham, NC, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhu, Davidson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Davidson","raw_affiliation_strings":["Duke University, Durham, NC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University, Durham, NC, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36340079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T11031","display_name":"Game Theory and Applications","score":0.6915000081062317,"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"}},"topics":[{"id":"https://openalex.org/T11031","display_name":"Game Theory and Applications","score":0.6915000081062317,"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":0.09070000052452087,"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/T11182","display_name":"Auction Theory and Applications","score":0.06679999828338623,"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":0.8970999717712402},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.6496999859809875},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5730999708175659},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5296000242233276},{"id":"https://openalex.org/keywords/characterization","display_name":"Characterization (materials science)","score":0.45879998803138733},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.4422000050544739},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.41119998693466187},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.41029998660087585},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.3986999988555908},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.384799987077713}],"concepts":[{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.8970999717712402},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.6496999859809875},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5730999708175659},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5429999828338623},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5414999723434448},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5296000242233276},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.45879998803138733},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4422000050544739},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.41119998693466187},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.41029998660087585},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3986999988555908},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.384799987077713},{"id":"https://openalex.org/C113138325","wikidata":"https://www.wikidata.org/wiki/Q864457","display_name":"Knapsack problem","level":2,"score":0.37700000405311584},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.36640000343322754},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.36059999465942383},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.3513999879360199},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C58694771","wikidata":"https://www.wikidata.org/wiki/Q814385","display_name":"Bounded rationality","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C145691206","wikidata":"https://www.wikidata.org/wiki/Q747980","display_name":"Polytope","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C205706631","wikidata":"https://www.wikidata.org/wiki/Q2319304","display_name":"Expected utility hypothesis","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.3276999890804291},{"id":"https://openalex.org/C21031990","wikidata":"https://www.wikidata.org/wiki/Q355020","display_name":"Probability measure","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.30410000681877136},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C91810955","wikidata":"https://www.wikidata.org/wiki/Q7731670","display_name":"Incentive compatibility","level":3,"score":0.25529998540878296}],"mesh":[],"locations_count":5,"locations":[{"id":"pmh:oai:arXiv.org:2511.08538","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.08538","pdf_url":"https://arxiv.org/pdf/2511.08538","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:doi:10.4230/lipics.forc.2026.14","is_oa":true,"landing_page_url":"https://proceedings.neurips.cc/paper/2021/hash/63c3ddcc7b23daa1e42dc41f9a44a873-Abstract.html","pdf_url":"https://proceedings.neurips.cc/paper_files/paper/2021/file/63c3ddcc7b23daa1e42dc41f9a44a873-Paper.pdf","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"ConferencePaper"},{"id":"pmh:oai:drops-oai.dagstuhl.de:25987","is_oa":true,"landing_page_url":"https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FORC.2026.14","pdf_url":"https://drops.dagstuhl.de/storage/00lipics/lipics-vol368-forc2026/LIPIcs.FORC.2026.14/LIPIcs.FORC.2026.14.pdf","source":{"id":"https://openalex.org/S4377196569","display_name":"DROPS (Schloss Dagstuhl \u2013 Leibniz Center for Informatics)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2799853480","host_organization_name":"Schloss Dagstuhl \u2013 Leibniz Center for Informatics","host_organization_lineage":["https://openalex.org/I2799853480"],"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":null,"raw_type":"publishedVersion"},{"id":"doi:10.48550/arxiv.2511.08538","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.08538","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"},{"id":"doi:10.4230/lipics.forc.2026.14","is_oa":true,"landing_page_url":"https://doi.org/10.4230/lipics.forc.2026.14","pdf_url":null,"source":{"id":"https://openalex.org/S7407052059","display_name":"Dagstuhl Research Online Publication Server","issn_l":null,"issn":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":""}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2511.08538","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.08538","pdf_url":"https://arxiv.org/pdf/2511.08538","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3726663184","display_name":"III: Medium: Collaborative Research: Counterfactual Learning and Evaluation for Interactive Information Systems","funder_award_id":"1901168","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5343391011","display_name":null,"funder_award_id":"IIS-1901168","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5410816779","display_name":null,"funder_award_id":"IIS-2008139","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6797014441","display_name":"III: Small: Fairness and Control of Exposure in Ranking","funder_award_id":"2008139","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7257828944","display_name":"III: Medium: Responsive Optimization for Algorithmic Decision Systems","funder_award_id":"2402823","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416377607.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,12,106,129],"study":[1],"the":[2,7,38,44,47,60,65,68,72,104,108,112,115,126,142,183,194,230],"problem":[3],"of":[4,9,37,46,71,103,174,185,197,206],"selection":[5,48],"in":[6,150,225],"context":[8],"Bayesian":[10],"persuasion.":[11],"are":[13],"given":[14,124,190],"multiple":[15],"agents":[16,73,116],"with":[17,35],"hidden":[18],"values":[19,40],"(or":[20],"quality":[21],"scores),":[22],"to":[23,42,114,118,219],"whom":[24],"resources":[25],"must":[26],"be":[27,205,223],"allocated":[28],"by":[29,49,125],"a":[30,131,136,145,178,189,198,201],"welfare-maximizing":[31],"decision-maker.":[32],"An":[33],"intermediary":[34],"knowledge":[36],"agents'":[39],"seeks":[41],"influence":[43],"outcome":[45],"designing":[50],"informative":[51],"signals":[52],"and":[53,160],"providing":[54],"tie-breaking":[55],"policies,":[56],"so":[57],"that":[58,161,166,182,203,213],"when":[59],"receiver":[61],"maximizes":[62,97],"welfare":[63],"over":[64],"resulting":[66],"posteriors,":[67],"expected":[69],"utilities":[70,187],"(where":[74],"utility":[75],"is":[76,92,156,177],"defined":[77],"as":[78,123],"allocation":[79,113],"times":[80],"value)":[81],"achieve":[82],"certain":[83],"fairness":[84,87],"properties.":[85],"The":[86,153],"measure":[88],"we":[89,211],"will":[90],"use":[91],"majorization,":[93],"which":[94],"simultaneously":[95],"approximately":[96],"all":[98],"symmetric,":[99],"monotone,":[100],"concave":[101],"functions":[102],"utilities.":[105],"consider":[107],"general":[109],"setting":[110],"where":[111],"needs":[117],"respect":[119],"arbitrary":[120],"submodular":[121],"constraints,":[122],"corresponding":[127],"polymatroid.":[128],"present":[130],"signaling":[132,191],"policy":[133,149,192],"that,":[134],"under":[135],"mild":[137],"bounded":[138],"rationality":[139],"assumption":[140],"on":[141],"receiver,":[143],"achieves":[144],"logarithmically":[146],"approximate":[147],"majorized":[148],"this":[151,220],"setting.":[152],"approximation":[154,218],"ratio":[155],"almost":[157],"best":[158],"possible,":[159],"significantly":[162],"outperforms":[163],"generic":[164],"results":[165],"only":[167],"yield":[168],"linear":[169],"approximations.":[170],"A":[171],"key":[172],"component":[173],"our":[175],"result":[176,202],"structural":[179],"characterization":[180],"showing":[181],"vector":[184,221],"agent":[186],"for":[188],"defines":[193],"base":[195],"polytope":[196],"different":[199],"polymatroid,":[200],"may":[204],"independent":[207],"interest.":[208],"In":[209],"addition,":[210],"show":[212],"an":[214],"arbitrarily":[215],"good":[216],"additive":[217],"can":[222],"produced":[224],"(weakly)":[226],"polynomial":[227],"time":[228],"via":[229],"multiplicative":[231],"weights":[232],"update":[233],"method.":[234]},"counts_by_year":[],"updated_date":"2026-06-22T08:00:12.763002","created_date":"2025-11-13T00:00:00"}
