The Metric Distortion of Randomized Social Choice Functions: C1 Maximal Lottery Rules and Simulations

TL;DR

This paper analyzes the metric distortion of randomized social choice functions, showing C1 maximal lottery rules have optimal distortion of 4, and provides empirical and analytical insights into their average-case performance.

Contribution

The paper establishes the optimal metric distortion of C1 maximal lottery rules and offers new computational and analytical methods to evaluate average-case distortion.

Findings

C1 maximal lottery rules have a metric distortion of 4, which is optimal among majoritarian RSCFs.

Computer experiments show classical RSCFs have average-case distortion close to distortion-minimizing rules.

Under impartial culture, the expected distortion of RSCFs approaches 2 as the number of voters grows.

Abstract

The metric distortion of a randomized social choice function (RSCF) quantifies its worst-case approximation ratio to the optimal social cost when the voters' costs for alternatives are given by distances in a metric space. This notion has recently attracted significant attention as numerous RSCFs that aim to minimize the metric distortion have been suggested. Since such tailored voting rules have, however, little normative appeal other than their low metric distortion, we will study the metric distortion of well-established RSCFs. Specifically, we first show that C1 maximal lottery rules, a well-known class of RSCFs, have a metric distortion of $4$, which is optimal within the class of majoritarian RSCFs. Secondly, we conduct extensive computer experiments on the metric distortion of RSCFs to obtain insights into their average-case performance. These computer experiments are based on a new linear program for computing the metric distortion of a lottery and reveal that the average-case metric distortion of some classical RSCFs is often only slightly worse than that of RSCFs tailored to minimize the metric distortion. Finally, we also analytically study the expected metric distortion of RSCFs for the impartial culture distribution. Specifically, we show that, under this distribution, every reasonable RSCF has an expected metric distortion close to $2$ when the number of voters is large.