{"id":"https://openalex.org/W4221161935","doi":"https://doi.org/10.1145/3490486.3538313","title":"Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning","display_name":"Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning","publication_year":2022,"publication_date":"2022-07-12","ids":{"openalex":"https://openalex.org/W4221161935","doi":"https://doi.org/10.1145/3490486.3538313"},"language":"en","primary_location":{"id":"doi:10.1145/3490486.3538313","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490486.3538313","pdf_url":null,"source":{"id":"https://openalex.org/S4363608973","display_name":"Proceedings of the 23rd ACM Conference on Economics and Computation","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Economics and Computation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010684754","display_name":"Jibang Wu","orcid":"https://orcid.org/0000-0002-1087-5893"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jibang Wu","raw_affiliation_strings":["University of Virginia, Charlottesville, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100321161","display_name":"Zixuan Zhang","orcid":"https://orcid.org/0000-0001-9987-1137"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixuan Zhang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038547295","display_name":"Zhe Chuan Feng","orcid":"https://orcid.org/0000-0002-8982-8757"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe Feng","raw_affiliation_strings":["Google, Mountain View, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101934110","display_name":"Zhaoran Wang","orcid":"https://orcid.org/0000-0002-1824-2580"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaoran Wang","raw_affiliation_strings":["Northwestern University, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University, Chicago, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101727948","display_name":"Zhuoran Yang","orcid":"https://orcid.org/0000-0001-5269-9958"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhuoran Yang","raw_affiliation_strings":["Yale University, New Haven, CT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049812527","display_name":"Michael I. Jordan","orcid":"https://orcid.org/0000-0001-8935-817X"},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael I. Jordan","raw_affiliation_strings":["UC Berkeley, Berkeley, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100731919","display_name":"Haifeng Xu","orcid":"https://orcid.org/0000-0003-1538-6957"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]},{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haifeng Xu","raw_affiliation_strings":["University of Chicago, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238","https://openalex.org/I40347166"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.309,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7878322,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"471","last_page":"472"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T12238","display_name":"Green IT and Sustainability","score":0.9743000268936157,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.9621000289916992,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/communication-source","display_name":"Communication source","score":0.79256272315979},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7405923008918762},{"id":"https://openalex.org/keywords/persuasion","display_name":"Persuasion","score":0.7203778028488159},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6740810871124268},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.6714547872543335},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.6370340585708618},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5084328055381775},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4700578451156616},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.4567990303039551},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4243970811367035},{"id":"https://openalex.org/keywords/complete-information","display_name":"Complete information","score":0.4236070513725281},{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.4104975461959839},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4073985815048218},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.1948845386505127},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1669713854789734},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.1491956114768982},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11704421043395996},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.11665350198745728},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11571750044822693}],"concepts":[{"id":"https://openalex.org/C198104137","wikidata":"https://www.wikidata.org/wiki/Q974688","display_name":"Communication source","level":2,"score":0.79256272315979},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7405923008918762},{"id":"https://openalex.org/C2781310500","wikidata":"https://www.wikidata.org/wiki/Q1231428","display_name":"Persuasion","level":2,"score":0.7203778028488159},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6740810871124268},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.6714547872543335},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.6370340585708618},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5084328055381775},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4700578451156616},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.4567990303039551},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4243970811367035},{"id":"https://openalex.org/C113336015","wikidata":"https://www.wikidata.org/wiki/Q574010","display_name":"Complete information","level":2,"score":0.4236070513725281},{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.4104975461959839},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4073985815048218},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.1948845386505127},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1669713854789734},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.1491956114768982},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11704421043395996},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.11665350198745728},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11571750044822693},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3490486.3538313","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3490486.3538313","pdf_url":null,"source":{"id":"https://openalex.org/S4363608973","display_name":"Proceedings of the 23rd ACM Conference on Economics and Computation","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Economics and Computation","raw_type":"proceedings-article"},{"id":"pmh:oai:RePEc:arx:papers:2202.10678","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"preprint"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3563229189","display_name":null,"funder_award_id":"2048075 2008827 2015568 1934931","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G405407587","display_name":null,"funder_award_id":"CCF-2132506","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":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1193337282","https://openalex.org/W1662240627","https://openalex.org/W2161303371","https://openalex.org/W3169835994","https://openalex.org/W1546646725","https://openalex.org/W2491046942","https://openalex.org/W2023420517","https://openalex.org/W187740018","https://openalex.org/W2162286586","https://openalex.org/W4255368532"],"abstract_inverted_index":{"In":[0],"today's":[1],"economy,":[2],"it":[3,125],"becomes":[4],"important":[5],"for":[6],"Internet":[7],"platforms":[8],"to":[9,16,56,63,101],"consider":[10],"the":[11,25,43,68,89,102,107,113,117,121,133,150],"sequential":[12,39],"information":[13,40],"design":[14],"problem":[15],"align":[17],"its":[18],"long":[19],"term":[20],"interest":[21],"with":[22,52,78,138],"incentives":[23],"of":[24,38,60,112,149],"gig":[26],"service":[27],"providers":[28],"(e.g.,":[29],"drivers,":[30],"hosts).":[31],"This":[32],"paper":[33],"proposes":[34],"a":[35,50,58,73,94,146],"novel":[36],"model":[37,122],"design,":[41],"namely":[42],"Markov":[44],"persuasion":[45],"processes":[46],"(MPPs),":[47],"in":[48,72,85,92,116],"which":[49],"sender,":[51],"informational":[53],"advantage,":[54],"seeks":[55],"persuade":[57],"stream":[59],"myopic":[61,103],"receivers":[62,104],"take":[64],"actions":[65],"that":[66,97,128,153],"maximize":[67],"sender's":[69],"cumulative":[70,110],"utilities":[71,111],"finite":[74,139],"horizon":[75],"Markovian":[76],"environment":[77],"varying":[79],"prior":[80],"and":[81,105,143],"utility":[82],"functions.":[83],"Planning":[84],"MPPs":[86],"thus":[87],"faces":[88],"unique":[90],"challenge":[91],"finding":[93],"signaling":[95],"policy":[96,137],"is":[98,123],"simultaneously":[99],"persuasive":[100],"inducing":[106],"optimal":[108,134],"long-term":[109],"sender.":[114],"Nevertheless,":[115],"population":[118],"level":[119],"where":[120],"known,":[124],"turns":[126],"out":[127],"we":[129],"can":[130],"efficiently":[131],"determine":[132],"(resp.":[135,140],"\u03b5-optimal)":[136],"infinite)":[141],"states":[142],"outcomes,":[144],"through":[145],"modified":[147],"formulation":[148],"Bellman":[151],"equation":[152],"additionally":[154],"takes":[155],"persuasiveness":[156],"into":[157],"consideration.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}