Voting on multi-issue domains with conditionally lexicographic preferences

Jérôme Lang (1) , Jérôme Mengin (2) , Lirong Xia (3)

1 Université Paris Dauphine-PSL
2 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
3 Rensslaer Polytechnic Institute, USA

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

Mots clés: Maximum satisfiability; Voting; Computational social choice; Winner determination; Lexicographic preferences

Domaines: Intelligence artificielle [cs.AI]

Jérôme Lang, Jérôme Mengin, Lirong Xia. Voting on multi-issue domains with conditionally lexicographic preferences. Artificial Intelligence, 2018, 265, pp.18-44. ⟨10.1016/j.artint.2018.05.004⟩. ⟨hal-02147965⟩