论文标题
同行代表委员会
Representative Committees of Peers
论文作者
论文摘要
一群选民必须选举自己的代表，以决定一系列可能无法预料的二元问题。选民只关心最终决定，而不是当选代表。选民的分离与问题的比例成正比，在此，他的偏好不同意这一决定。 尽管所有选民的逐个发行投票都将最大化社会福利，但我们对小型委员会近似人口偏好的偏好程度感兴趣。 我们表明，k级（委员会内有多数投票的K选民的随机委员会）导致在任何数量的选民n，任何数量的问题$ m $和任何优先档案中的最佳社会成本的因子1+O（1/k）中取得结果。 对于少数问题，可以通过委托程序根据委员会成员的追随者数量来使社会成本更接近最佳。但是，对于大m，我们证明了K态是广泛的基于委员会规则的广泛家庭中最糟糕的最佳规则，该规则考虑了有关整个人群偏好概况的指标信息。
A population of voters must elect representatives among themselves to decide on a sequence of possibly unforeseen binary issues. Voters care only about the final decision, not the elected representatives. The disutility of a voter is proportional to the fraction of issues, where his preferences disagree with the decision. While an issue-by-issue vote by all voters would maximize social welfare, we are interested in how well the preferences of the population can be approximated by a small committee. We show that a k-sortition (a random committee of k voters with the majority vote within the committee) leads to an outcome within the factor 1+O(1/k) of the optimal social cost for any number of voters n, any number of issues $m$, and any preference profile. For a small number of issues m, the social cost can be made even closer to optimal by delegation procedures that weigh committee members according to their number of followers. However, for large m, we demonstrate that the k-sortition is the worst-case optimal rule within a broad family of committee-based rules that take into account metric information about the preference profile of the whole population.
