发表机构
Rutgers University; Stanford University; Harvard University（罗格斯大学; 斯坦福大学; 哈佛大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种基于零和博弈单一分布的随机投票规则，实现度量失真至多2.13713，接近理论下界，并证明稳定2-抽签失真为7/3。
AI 中文摘要
我们证明了存在一种随机投票规则，其度量失真至多为$2.13713$，与下界$2.11264$相差$0.025$以内。我们的规则源于在委员会选择背景下发展的稳定$k$-抽签的推广。与先前工作不同，我们的规则从由零和博弈导出的单一分布中采样，而不在投票规则之间混合。我们的结果还为稳定$k$-抽签提供了尖锐的失真界限，特别表明稳定$2$-抽签的失真为$7/3$，尽管仅依赖于对候选三元组的聚合偏好。
英文摘要
We prove the existence of a randomized voting rule with metric distortion at most $2.13713$, within $0.025$ of the lower bound of $2.11264$. Our rule comes from a generalization of stable $k$-lotteries developed in the context of committee selection. In contrast to prior work, our rule samples from a single distribution derived from a zero-sum game, without mixing between voting rules. Our result also gives sharp distortion bounds for stable $k$-lotteries, and in particular shows that stable $2$-lotteries have distortion $7/3$, despite only relying on aggregate preferences over triples of candidates.
