Communication, Distortion, and Randomness in Metric Voting
Abstract
In distortionbased analysis of social choice rules over metric spaces, one assumes that all voters and candidates are jointly embedded in a common metric space. Voters rank candidates by nondecreasing distance. The mechanism, receiving only this ordinal (comparison) information, should select a candidate approximately minimizing the sum of distances from all voters. It is known that while the Copeland rule and related rules guarantee distortion at most 5, many other standard voting rules, such as Plurality, Veto, or $k$approval, have distortion growing unboundedly in the number $n$ of candidates. Plurality, Veto, or $k$approval with small $k$ require less communication from the voters than all deterministic social choice rules known to achieve constant distortion. This motivates our study of the tradeoff between the distortion and the amount of communication in deterministic social choice rules. We show that any oneround deterministic voting mechanism in which each voter communicates only the candidates she ranks in a given set of $k$ positions must have distortion at least $\frac{2nk}{k}$; we give a mechanism achieving an upper bound of $O(n/k)$, which matches the lower bound up to a constant. For more general communicationbounded voting mechanisms, in which each voter communicates $b$ bits of information about her ranking, we show a slightly weaker lower bound of $\Omega(n/b)$ on the distortion. For randomized mechanisms, it is known that Random Dictatorship achieves expected distortion strictly smaller than 3, almost matching a lower bound of $3\frac{2}{n}$ for any randomized mechanism that only receives each voter's top choice. We close this gap, by giving a simple randomized social choice rule which only uses each voter's first choice, and achieves expected distortion $3\frac{2}{n}$.
 Publication:

arXiv eprints
 Pub Date:
 November 2019
 arXiv:
 arXiv:1911.08129
 Bibcode:
 2019arXiv191108129K
 Keywords:

 Computer Science  Computer Science and Game Theory;
 Computer Science  Discrete Mathematics;
 Economics  Theoretical Economics
 EPrint:
 An abbreviated version appear in Proceedings of AAAI 2020