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arXiv · 2002.01776

Evaluating approval-based multiwinner voting in terms of robustness to noise

Ioannis Caragiannis·Christos Kaklamanis·Nikos Karanikolas·George A. Krimpas
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Abstract

Approval-based multiwinner voting rules have recently received much attention in the Computational Social Choice literature. Such rules aggregate approval ballots and determine a winning committee of alternatives. To assess effectiveness, we propose to employ new noise models that are specifically tailored for approval votes and committees. These models take as input a ground truth committee and return random approval votes to be thought of as noisy estimates of the ground truth. A minimum robustness requirement for an approval-based multiwinner voting rule is to return the ground truth when applied to profiles with sufficiently many noisy votes. Our results indicate that approval-based multiwinner voting is always robust to reasonable noise. We further refine this finding by presenting a hierarchy of rules in terms of how robust to noise they are.

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Ioannis Caragiannis, Christos Kaklamanis, Nikos Karanikolas, George A. Krimpas. 2020-02-05. Evaluating approval-based multiwinner voting in terms of robustness to noise. https://arxiv.org/abs/2002.01776

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