Emergent Mind

Multiwinner Elections under Minimax Chamberlin-Courant Rule in Euclidean Space

(2205.13598)
Published May 26, 2022 in cs.GT and cs.CG

Abstract

We consider multiwinner elections in Euclidean space using the minimax Chamberlin-Courant rule. In this setting, voters and candidates are embedded in a $d$-dimensional Euclidean space, and the goal is to choose a committee of $k$ candidates so that the rank of any voter's most preferred candidate in the committee is minimized. (The problem is also equivalent to the ordinal version of the classical $k$-center problem.) We show that the problem is NP-hard in any dimension $d \geq 2$, and also provably hard to approximate. Our main results are three polynomial-time approximation schemes, each of which finds a committee with provably good minimax score. In all cases, we show that our approximation bounds are tight or close to tight. We mainly focus on the $1$-Borda rule but some of our results also hold for the more general $r$-Borda.

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