Tight approximation for proportional approval voting

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Abstract

In approval-based multiwinner elections, we are given a set of voters, a set of candidates, and, for each voter, a set of candidates approved by the voter. The goal is to find a committee of size k that maximizes the total utility of the voters. In this paper, we study approximability of Thiele rules, which are known to be NP-hard to solve exactly. We provide a tight polynomial time approximation algorithm for a natural class of geometrically dominant weights that includes such voting rules as Proportional Approval Voting or p-Geometric. The algorithm is relatively simple: first we solve a linear program and then we round a solution by employing a framework called pipage rounding due to Ageev and Sviridenko (2004) and Calinescu et al. (2011). We provide a matching lower bound via a reduction from the Label Cover problem. Moreover, assuming a conjecture called Gap-ETH, we show that better approximation ratio cannot be obtained even in time f(k)*pow(n,o(k)).

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Dudycz, S., Manurangsi, P., Marcinkowski, J., & Sornat, K. (2020). Tight approximation for proportional approval voting. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 2021-January, pp. 276–282). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2020/39

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