{"id":"https://openalex.org/W2903753352","doi":"https://doi.org/10.1609/aaai.v33i01.33011885","title":"Online Pandora\u2019s Boxes and Bandits","display_name":"Online Pandora\u2019s Boxes and Bandits","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2903753352","doi":"https://doi.org/10.1609/aaai.v33i01.33011885","mag":"2903753352"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33011885","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33011885","pdf_url":"https://www.aaai.org/ojs/index.php/AAAI/article/download/4014/3892","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.aaai.org/ojs/index.php/AAAI/article/download/4014/3892","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047480720","display_name":"Hossein Esfandiari","orcid":"https://orcid.org/0000-0001-8130-6631"},"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":"Hossein Esfandiari","raw_affiliation_strings":["Google Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108944480","display_name":"MohammadTaghi Hajiaghayi","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"MohammadTaghi HajiAghayi","raw_affiliation_strings":["University of Maryland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082964830","display_name":"Brendan Lucier","orcid":"https://orcid.org/0009-0006-3497-0875"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I4400600948","display_name":"Microsoft Research New England (United States)","ror":"https://ror.org/010wkqn50","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4400600948"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Brendan Lucier","raw_affiliation_strings":["Microsoft Research New England"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research New England","institution_ids":["https://openalex.org/I4210164937","https://openalex.org/I4400600948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062318856","display_name":"Michael Mitzenmacher","orcid":"https://orcid.org/0000-0001-5430-5457"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Mitzenmacher","raw_affiliation_strings":["Harvard University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard University","institution_ids":["https://openalex.org/I2801851002"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"01","first_page":"1885","last_page":"1892"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11182","display_name":"Auction Theory and Applications","score":0.9991999864578247,"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/T11182","display_name":"Auction Theory and Applications","score":0.9991999864578247,"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/T10646","display_name":"Experimental Behavioral Economics Studies","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9836999773979187,"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/knapsack-problem","display_name":"Knapsack problem","score":0.7105478644371033},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6273741722106934},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.6015549302101135},{"id":"https://openalex.org/keywords/secretary-problem","display_name":"Secretary problem","score":0.5703247785568237},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4745900332927704},{"id":"https://openalex.org/keywords/matroid","display_name":"Matroid","score":0.46317818760871887},{"id":"https://openalex.org/keywords/submodular-set-function","display_name":"Submodular set function","score":0.4593307375907898},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.44830504059791565},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4177580773830414},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4175138473510742},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3792403042316437},{"id":"https://openalex.org/keywords/operations-research","display_name":"Operations research","score":0.3273089528083801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3137344717979431},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2329203188419342},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19469597935676575},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16321682929992676},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.11938679218292236}],"concepts":[{"id":"https://openalex.org/C113138325","wikidata":"https://www.wikidata.org/wiki/Q864457","display_name":"Knapsack problem","level":2,"score":0.7105478644371033},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6273741722106934},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.6015549302101135},{"id":"https://openalex.org/C183211740","wikidata":"https://www.wikidata.org/wiki/Q1372364","display_name":"Secretary problem","level":3,"score":0.5703247785568237},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4745900332927704},{"id":"https://openalex.org/C106286213","wikidata":"https://www.wikidata.org/wiki/Q898572","display_name":"Matroid","level":2,"score":0.46317818760871887},{"id":"https://openalex.org/C178621042","wikidata":"https://www.wikidata.org/wiki/Q7631710","display_name":"Submodular set function","level":2,"score":0.4593307375907898},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.44830504059791565},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4177580773830414},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4175138473510742},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3792403042316437},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3273089528083801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3137344717979431},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2329203188419342},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19469597935676575},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16321682929992676},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.11938679218292236},{"id":"https://openalex.org/C99414536","wikidata":"https://www.wikidata.org/wiki/Q7098950","display_name":"Optimal stopping","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v33i01.33011885","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33011885","pdf_url":"https://www.aaai.org/ojs/index.php/AAAI/article/download/4014/3892","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/4014","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33011885","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33011885","pdf_url":"https://www.aaai.org/ojs/index.php/AAAI/article/download/4014/3892","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G1023616090","display_name":null,"funder_award_id":"CCF-1563710","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1406720844","display_name":"AF: Medium: Collaborative Research: General Frameworks for Approximation and Fixed-Parameter Algorithms","funder_award_id":"1161365","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G368365289","display_name":null,"funder_award_id":"CCF-1161365","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4284462045","display_name":"CIF: NeTS: Medium: Collaborative Research: Unifying Data Synchronization","funder_award_id":"1563710","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4425768753","display_name":"CAREER: Foundations of Network Design: Real-World Networks, Special Topologies, and Game Theory","funder_award_id":"1053605","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4486344550","display_name":"SPX: Collaborative Research: Moving Towards Secure and Massive Parallel Computing","funder_award_id":"1822738","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6050657354","display_name":null,"funder_award_id":"CNS-1228598","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6133564518","display_name":null,"funder_award_id":"CCF-1535795","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6289631934","display_name":"AF: Small: Data Synchronization : Theory, Algorithms, and Practice","funder_award_id":"1320231","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6578124655","display_name":null,"funder_award_id":"CCF-1320231","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6647242665","display_name":"TWC: Medium: Collaborative: Privacy-Preserving Distributed Storage and Computation","funder_award_id":"1228598","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6671297155","display_name":null,"funder_award_id":"CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7416083152","display_name":"BIGDATA: Collaborative Research: F: Making Big Data Accessible on Personal Devices: Big Network Algorithms, External Memory, and Data Streams","funder_award_id":"1546108","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7585794545","display_name":null,"funder_award_id":"CCF-1053605","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8352357737","display_name":null,"funder_award_id":"IIS-1546108","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8648019094","display_name":"AitF: FULL: Collaborative Research: Better Hashing for Applications:  From Nuts & Bolts to Asymptotics","funder_award_id":"1535795","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G957606086","display_name":null,"funder_award_id":"CCF-1822738","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"},{"id":"https://openalex.org/F4320308943","display_name":"Microsoft Research","ror":"https://ror.org/00d0nc645"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2903753352.pdf","grobid_xml":"https://content.openalex.org/works/W2903753352.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W122351777","https://openalex.org/W1530458910","https://openalex.org/W1892690425","https://openalex.org/W1981530653","https://openalex.org/W1999069228","https://openalex.org/W2011730242","https://openalex.org/W2012672170","https://openalex.org/W2022013502","https://openalex.org/W2034828004","https://openalex.org/W2060049918","https://openalex.org/W2104224720","https://openalex.org/W2113654320","https://openalex.org/W2117344175","https://openalex.org/W2150582214","https://openalex.org/W2179880041","https://openalex.org/W2266462034","https://openalex.org/W2949112440","https://openalex.org/W2949904805","https://openalex.org/W2963159830","https://openalex.org/W2963515037","https://openalex.org/W2964293104","https://openalex.org/W3122503641","https://openalex.org/W3123723491","https://openalex.org/W6646023306","https://openalex.org/W6653474156","https://openalex.org/W6658959670","https://openalex.org/W6680013454","https://openalex.org/W6682063461","https://openalex.org/W6745711171","https://openalex.org/W6780401969","https://openalex.org/W6986688003"],"related_works":["https://openalex.org/W4252399622","https://openalex.org/W4320232260","https://openalex.org/W1499990180","https://openalex.org/W4241672388","https://openalex.org/W2760293708","https://openalex.org/W3135330276","https://openalex.org/W4287979081","https://openalex.org/W4321600307","https://openalex.org/W4378471316","https://openalex.org/W2944744777"],"abstract_inverted_index":{"We":[0,82,116,136],"consider":[1,117,138],"online":[2,59,168],"variations":[3,118,139],"of":[4,21,112,160,163,171],"the":[5,19,30,36,75,92,113,158,161,167,190],"Pandora\u2019s":[6,32],"box":[7,33,64],"problem":[8,27,34],"(Weitzman":[9],"1979),":[10],"a":[11,46,152,186],"standard":[12],"model":[13],"for":[14,24,84],"understanding":[15],"issues":[16,159],"related":[17,140],"to":[18,61,73,104,108,126,141,174,189],"cost":[20,50,162],"acquiring":[22,164],"information":[23,165],"decision-making.":[25],"Our":[26,149,176],"generalizes":[28],"both":[29],"classic":[31,142],"and":[35,49,68,99],"prophet":[37],"inequality":[38],"framework.":[39],"Boxes":[40],"are":[41],"presented":[42],"online,":[43],"each":[44,63],"with":[45],"random":[47],"value":[48,114],"drawn":[51],"jointly":[52],"from":[53,146,166],"some":[54],"known":[55],"distribution.":[56],"Pandora":[57,120,183],"chooses":[58,70],"whether":[60,72],"open":[62,109],"given":[65],"its":[66],"cost,":[67],"then":[69],"irrevocably":[71],"keep":[74],"revealed":[76],"prize":[77,94],"or":[78,133],"pass":[79],"on":[80],"it.":[81],"aim":[83],"approximation":[85,188],"algorithms":[86],"against":[87],"adversaries":[88],"that":[89,179],"can":[90,121,184],"choose":[91],"largest":[93],"over":[95],"any":[96],"opened":[97],"box,":[98],"use":[100,151],"optimal":[101],"offline":[102],"policies":[103],"decide":[105],"which":[106,172],"boxes":[107],"(without":[110],"knowledge":[111],"inside)1.":[115],"where":[119,155],"collect":[122],"multiple":[123],"prizes":[124,173],"subject":[125],"feasibility":[127],"constraints,":[128],"such":[129],"as":[130],"cardinality,":[131],"matroid,":[132],"knapsack":[134],"constraints.":[135],"also":[137],"multi-armed":[143],"bandit":[144],"problems":[145],"reinforcement":[147],"learning.":[148],"results":[150],"reduction-based":[153],"framework":[154],"we":[156],"separate":[157],"decision":[169],"process":[170],"keep.":[175],"work":[177],"shows":[178],"in":[180],"many":[181],"scenarios,":[182],"achieve":[185],"good":[187],"best":[191],"possible":[192],"performance.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
