TY - JOUR
T1 - On the Computational Complexity of Non-Dictatorial Aggregation
AU - Kirousis, Lefteris
AU - Kolaitis, Phokion G.
AU - Livieratos, John
N1 - Publisher Copyright:
©2021 AI Access Foundation. All rights reserved.
PY - 2021
Y1 - 2021
N2 - We investigate when non-dictatorial aggregation is possible from an algorithmic perspective, where non-dictatorial aggregation means that the votes cast by the members of a society can be aggregated in such a way that there is no single member of the society that always dictates the collective outcome. We consider the setting in which the members of a society take a position on a fixed collection of issues, where for each issue several different alternatives are possible, but the combination of choices must belong to a given set X of allowable voting patterns. Such a set X is called a possibility domain if there is an aggregator that is non-dictatorial, operates separately on each issue, and returns values among those cast by the society on each issue. We design a polynomial-time algorithm that decides, given a set X of voting patterns, whether or not X is a possibility domain. Furthermore, if X is a possibility domain, then the algorithm constructs in polynomial time a non-dictatorial aggregator for X. Furthermore, we show that the question of whether a Boolean domain X is a possibility domain is in NLOGSPACE. We also design a polynomial-time algorithm that decides whether X is a uniform possibility domain, that is, whether X admits an aggregator that is non-dictatorial even when restricted to any two positions for each issue. As in the case of possibility domains, the algorithm also constructs in polynomial time a uniform non-dictatorial aggregator, if one exists. Then, we turn our attention to the case where X is given implicitly, either as the set of assignments satisfying a propositional formula, or as a set of consistent evaluations of a sequence of propositional formulas. In both cases, we provide bounds to the complexity of deciding if X is a (uniform) possibility domain. Finally, we extend our results to four types of aggregators that have appeared in the literature: generalized dictatorships, whose outcome is always an element of their input, anonymous aggregators, whose outcome is not affected by permutations of their input, monotone, whose outcome does not change if more individuals agree with it and systematic, which aggregate every issue in the same way.
AB - We investigate when non-dictatorial aggregation is possible from an algorithmic perspective, where non-dictatorial aggregation means that the votes cast by the members of a society can be aggregated in such a way that there is no single member of the society that always dictates the collective outcome. We consider the setting in which the members of a society take a position on a fixed collection of issues, where for each issue several different alternatives are possible, but the combination of choices must belong to a given set X of allowable voting patterns. Such a set X is called a possibility domain if there is an aggregator that is non-dictatorial, operates separately on each issue, and returns values among those cast by the society on each issue. We design a polynomial-time algorithm that decides, given a set X of voting patterns, whether or not X is a possibility domain. Furthermore, if X is a possibility domain, then the algorithm constructs in polynomial time a non-dictatorial aggregator for X. Furthermore, we show that the question of whether a Boolean domain X is a possibility domain is in NLOGSPACE. We also design a polynomial-time algorithm that decides whether X is a uniform possibility domain, that is, whether X admits an aggregator that is non-dictatorial even when restricted to any two positions for each issue. As in the case of possibility domains, the algorithm also constructs in polynomial time a uniform non-dictatorial aggregator, if one exists. Then, we turn our attention to the case where X is given implicitly, either as the set of assignments satisfying a propositional formula, or as a set of consistent evaluations of a sequence of propositional formulas. In both cases, we provide bounds to the complexity of deciding if X is a (uniform) possibility domain. Finally, we extend our results to four types of aggregators that have appeared in the literature: generalized dictatorships, whose outcome is always an element of their input, anonymous aggregators, whose outcome is not affected by permutations of their input, monotone, whose outcome does not change if more individuals agree with it and systematic, which aggregate every issue in the same way.
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U2 - 10.1613/JAIR.1.12476
DO - 10.1613/JAIR.1.12476
M3 - Article
AN - SCOPUS:85117082098
SN - 1076-9757
VL - 72
SP - 137
EP - 183
JO - Journal of Artificial Intelligence Research
JF - Journal of Artificial Intelligence Research
ER -