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Voting on multi-issue domains with conditionally lexicographic preferences

Lang, Jérôme and Mengin, Jérôme and Xia, Lirong Voting on multi-issue domains with conditionally lexicographic preferences. (2018) Artificial Intelligence, 265. 18-44. ISSN 0004-3702

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Official URL: https://doi.org/10.1016/j.artint.2018.05.004

Abstract

One approach to voting on several interrelated issues consists in using a language for compact preference representation, from which the voters' preferences are elicited and aggregated. Such a language can usually be seen as a domain restriction. We consider a well-known restriction, namely, conditionally lexicographic preferences , where both the relative importance between issues and the preference between the values of an issue may depend on the values taken by more important issues. The naturally associated language consists in describing conditional importance and conditional preference by trees together with conditional preference tables. In this paper, we study the aggregation of conditionally lexicographic preferences for several common voting rules and several classes of lexicographic preferences. We address the computation of the winning alternative for some important rules, both by identifying the computational complexity of the relevant problems and by showing that for several of them, computing the winner reduces in a very natural way to a maxsat problem

Item Type:Article
HAL Id:hal-02147965
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Other partners > Rensselaer Polytechnic Institute - RPI (USA)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Université Paris-Dauphine (FRANCE)
Other partners > PSL Research University (FRANCE)
Laboratory name:
Funders:
Agence nationale de la recherche (FRANCE) - National Science Foundation (USA) - ONR : Office of Naval Research #N00014-17-1-2621 (USA)
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Deposited On:17 May 2019 13:08

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