The Distortion of Binomial Voting Defies Expectation
Computer Science and Game Theory
2023-12-11 v2 Artificial Intelligence
Abstract
In computational social choice, the distortion of a voting rule quantifies the degree to which the rule overcomes limited preference information to select a socially desirable outcome. This concept has been investigated extensively, but only through a worst-case lens. Instead, we study the expected distortion of voting rules with respect to an underlying distribution over voter utilities. Our main contribution is the design and analysis of a novel and intuitive rule, binomial voting, which provides strong distribution-independent guarantees for both expected distortion and expected welfare.
Cite
@article{arxiv.2306.15657,
title = {The Distortion of Binomial Voting Defies Expectation},
author = {Yannai A. Gonczarowski and Gregory Kehne and Ariel D. Procaccia and Ben Schiffer and Shirley Zhang},
journal= {arXiv preprint arXiv:2306.15657},
year = {2023}
}
Comments
NeurIPS 2023