On the complexity of winner verification and candidate winner for multiwinner voting rules

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Abstract

The Chamberlin-Courant and Monroe rules are fundamental and well-studied rules in the literature of multi-winner elections. The problem of determining if there exists a committee of size k that has a Chamberlin-Courant (respectively, Monroe) dissatisfaction score of at most r is known to be NP-complete. We consider the following natural problems in this setting: a) given a committee S of size k as input, is it an optimal k-sized committee, and b) given a candidate c and a committee size k, does there exist an optimal k-sized committee that contains c? In this work, we resolve the complexity of both problems for the Chamberlin-Courant and Monroe voting rules in the settings of rankings as well as approval ballots. We show that verifying if a given committee is optimal is coNP-complete whilst the latter problem is complete for TP2. Our contribution fills an essential gap in the literature for these important multi-winner rules.

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Sonar, C., Dey, P., & Misra, N. (2020). On the complexity of winner verification and candidate winner for multiwinner voting rules. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 2021-January, pp. 89–95). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2020/13

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