Simultaneous Elicitation of Committee and Voters' Preferences
Napolitano, Beatrice; Cailloux, Olivier; Viappiani, Paolo (2019), Simultaneous Elicitation of Committee and Voters' Preferences, in Lefrançois, Maxime, Actes des 17èmes Rencontres des Jeunes Chercheurs en Intelligence Artificielle (RJCIA 2019), Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, p. 59-62
Type
Communication / ConférenceExternal document link
https://hal.archives-ouvertes.fr/hal-02160455Date
2019Conference title
Rencontres des Jeunes Chercheurs en Intelligence Artificielle 2019Conference date
2019-07Conference city
ToulouseConference country
FranceBook title
Actes des 17èmes Rencontres des Jeunes Chercheurs en Intelligence Artificielle (RJCIA 2019)Book author
Lefrançois, MaximePublisher
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik
Pages
59-62
Metadata
Show full item recordAuthor(s)
Napolitano, BeatriceLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Cailloux, Olivier

Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Viappiani, Paolo

Abstract (EN)
Social choice deals with the problem of determining a consensus choice from the preferences of different voters. In the classical setting, the voting rule is fixed beforehand and full information concerning he preferences of the voters is provided. Recently, the assumption of full preference information has been questioned by a number of researchers and several methods for eliciting preferences have been proposed. In this paper we go one step further and we assume that both the voting rule and the voters’ preferences are partially specified. In this setting, we present an interactive elicitation protocol based on minimax regret and develop several query strategies that interleave questions to the chair and questions to the voters in order to attempt to acquire the most relevant information in order to quickly converge to optimal or a near-optimal alternative.Subjects / Keywords
Computational Social Choice; uncertainty in AI; minimax regret; preference elicitationRelated items
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