{"id":"https://openalex.org/W99643971","doi":"https://doi.org/10.5591/978-1-57735-516-8/ijcai11-058","title":"Robust approximation and incremental elicitation in voting protocols","display_name":"Robust approximation and incremental elicitation in voting protocols","publication_year":2011,"publication_date":"2011-07-16","ids":{"openalex":"https://openalex.org/W99643971","doi":"https://doi.org/10.5591/978-1-57735-516-8/ijcai11-058","mag":"99643971"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.208.2568","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.208.2568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ijcai.org/papers11/Papers/IJCAI11-058.pdf","raw_type":"text"},"type":"article","indexed_in":[],"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/A5086690493","display_name":"Tyler Lu","orcid":"https://orcid.org/0000-0002-7433-8421"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tyler Lu","raw_affiliation_strings":["University of Toronto, Department of Computer Science"],"raw_orcid":"https://orcid.org/0000-0002-7433-8421","affiliations":[{"raw_affiliation_string":"University of Toronto, Department of Computer Science","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036934218","display_name":"Craig Boutilier","orcid":"https://orcid.org/0000-0001-9330-4545"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Craig Boutilier","raw_affiliation_strings":["University of Toronto, Department of Computer Science"],"raw_orcid":"https://orcid.org/0000-0001-9330-4545","affiliations":[{"raw_affiliation_string":"University of Toronto, Department of Computer Science","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I185261750"],"apc_list":null,"apc_paid":null,"fwci":26.1269,"has_fulltext":false,"cited_by_count":115,"citation_normalized_percentile":{"value":0.9938597,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"287","last_page":"293"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10991","display_name":"Game Theory and Voting Systems","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"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/T10315","display_name":"Decision-Making and Behavioral Economics","score":0.9739999771118164,"subfield":{"id":"https://openalex.org/subfields/1800","display_name":"General Decision Sciences"},"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/regret","display_name":"Regret","score":0.9573514461517334},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.7782840132713318},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7093936204910278},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6470867991447449},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.6420542597770691},{"id":"https://openalex.org/keywords/preference-elicitation","display_name":"Preference elicitation","score":0.6176686882972717},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.606250524520874},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.42210888862609863},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4185599684715271},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3518182635307312},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3367624878883362},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2325781285762787},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09368309378623962}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.9573514461517334},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.7782840132713318},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7093936204910278},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470867991447449},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.6420542597770691},{"id":"https://openalex.org/C2777868144","wikidata":"https://www.wikidata.org/wiki/Q7239817","display_name":"Preference elicitation","level":3,"score":0.6176686882972717},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.606250524520874},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.42210888862609863},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4185599684715271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3518182635307312},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3367624878883362},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2325781285762787},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09368309378623962},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.208.2568","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.208.2568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ijcai.org/papers11/Papers/IJCAI11-058.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.301.8872","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.8872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.toronto.edu/~cebly/Papers/LuBoutilier_Elicitation_ijcai11.pdf","raw_type":"text"},{"id":"mag:99643971","is_oa":false,"landing_page_url":"https://www.cs.utoronto.ca/~cebly/Papers/LuBoutilier_Elicitation_ijcai11.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419999","display_name":"International Joint Conference on Artificial Intelligence","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":null,"is_accepted":false,"is_published":null,"raw_source_name":"International Joint Conference on Artificial Intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W107169386","https://openalex.org/W163449460","https://openalex.org/W1505652737","https://openalex.org/W1590250213","https://openalex.org/W1611302770","https://openalex.org/W1632943618","https://openalex.org/W1729393350","https://openalex.org/W2013327987","https://openalex.org/W2047793033","https://openalex.org/W2063445365","https://openalex.org/W2108077701","https://openalex.org/W2121751780","https://openalex.org/W2125530148","https://openalex.org/W2131369511","https://openalex.org/W2140970383","https://openalex.org/W2141733469","https://openalex.org/W2145996207"],"related_works":["https://openalex.org/W2047793033","https://openalex.org/W2121751780","https://openalex.org/W163449460","https://openalex.org/W2063445365","https://openalex.org/W1611302770","https://openalex.org/W2154896738","https://openalex.org/W2129678216","https://openalex.org/W2145996207","https://openalex.org/W2013327987","https://openalex.org/W2043715088","https://openalex.org/W3101083801","https://openalex.org/W1978753906","https://openalex.org/W1576809162","https://openalex.org/W58291377","https://openalex.org/W3015812362","https://openalex.org/W2265690809","https://openalex.org/W2003734769","https://openalex.org/W2127842795","https://openalex.org/W190528034","https://openalex.org/W43928053"],"abstract_inverted_index":{"While":[0],"voting":[1,70,101],"schemes":[2],"provide":[3],"an":[4],"effective":[5,13],"means":[6],"for":[7,11,60,67,91,119],"aggregating":[8],"preferences,":[9],"methods":[10],"the":[12,48,62,113],"elicitation":[14,86,118],"of":[15,52,116],"voter":[16,34,106],"preferences":[17,35,107],"have":[18],"received":[19],"little":[20],"attention.":[21],"We":[22,72],"address":[23],"this":[24,92],"problem":[25],"by":[26],"first":[27],"considering":[28],"approximate":[29,122],"winner":[30],"determination":[31],"when":[32],"incomplete":[33],"are":[36],"provided.":[37],"Exploiting":[38],"natural":[39],"scoring":[40],"metrics,":[41],"we":[42,111],"use":[43],"max":[44],"regret":[45,66,77],"to":[46,81,108],"measure":[47],"quality":[49],"or":[50],"robustness":[51],"proposed":[53],"winners,":[54,110],"and":[55,87,123],"develop":[56],"polynomial":[57],"time":[58],"algorithms":[59],"computing":[61],"alternative":[63],"with":[64],"minimax":[65,76],"several":[68,89,127],"popular":[69],"rules.":[71],"then":[73],"show":[74],"how":[75],"can":[78],"be":[79],"used":[80],"effectively":[82],"drive":[83],"incremental":[84],"preference/vote":[85],"devise":[88],"heuristics":[90],"process.":[93],"Despite":[94],"worst-case":[95],"theoretical":[96],"results":[97],"showing":[98],"that":[99],"most":[100],"protocols":[102],"require":[103],"nearly":[104],"complete":[105],"determine":[109],"demonstrate":[112],"practical":[114],"effectiveness":[115],"regret-based":[117],"determining":[120],"both":[121],"exact":[124],"winners":[125],"on":[126],"real-world":[128],"data":[129],"sets.":[130],"1":[131]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":16},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":16},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":7}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
