报告主题：在度量空间中淘汰最不受欢迎的候选人的投票
报告人：陈旭瑾 研究员 （中国科学院数学与系统科学研究院）
报告时间：2020年12月23日（周三） 15:15
会议形式：腾讯会议
会 议 ID：880 271 601
邀请人：康丽英
报告摘要： We study single-candidate voting embedded in a metric space, where both voters and candidates are points in the space, and the distances between voters and candidates specify the voters’ preferences over candidates. In the voting, each voter is asked to submit her favorite candidate. Given the collection of favorite candidates, a mechanism for eliminating the least popular candidate finds a committee containing all candidates but the one to be eliminated. Each committee is associated with a social value that is the sum of the costs (utilities) it imposes (provides) to the voters. We design mechanisms for finding a committee to optimize the social value. We measure the quality of a mechanism by its distortion, defined as the worst-case ratio between the social value of the committee found by the mechanism and the optimal one. We establish new upper and lower bounds on the distortion of mechanisms in this single-candidate voting, for both general metrics and well-motivated special cases.
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