Consider the following social choice problem. Suppose we have a set of $n$ voters and $m$ candidates that lie in a metric space. The goal is to design a mechanism to choose a candidate whose average distance to the voters is as small as possible. However, the mechanism does not get direct access to the metric space. Instead, it gets each voter's ordinal ranking of the candidates by distance. Given only this partial information, what is the smallest worst-case approximation ratio (known as the distortion) that a mechanism can guarantee? A simple example shows that no deterministic mechanism can guarantee distortion better than $3$, and no randomized mechanism can guarantee distortion better than $2$. It has been conjectured that both of these lower bounds are optimal, and recently, Gkatzelis, Halpern, and Shah proved this conjecture for deterministic mechanisms. We disprove the conjecture for randomized mechanisms for $m \geq 3$ by constructing elections for which no randomized mechanism can guarantee distortion better than $2.0261$ for $m = 3$, $2.0496$ for $m = 4$, up to $2.1126$ as $m \to \infty$. We obtain our lower bounds by identifying a class of simple metrics that appear to capture much of the hardness of the problem, and we show that any randomized mechanism must have high distortion on one of these metrics. We provide a nearly matching upper bound for this restricted class of metrics as well. Finally, we conjecture that these bounds give the optimal distortion for every $m$, and provide a proof for $m = 3$, thereby resolving that case.
翻译:考虑以下的社会选择问题 。 假设我们拥有一套 $ $ 的选民和 $ $ 候选人的一套机制。 目标是设计一个机制来选择一个与选民平均距离尽可能小于2美元的候选人。 但是, 机制无法直接进入度空间。 相反, 机制通过距离来获得每个选民候选人的交级排名。 仅凭这一片面信息, 一个机制可以保证什么是最小的最坏情况近似比率( 称为扭曲 )? 一个简单的例子显示, 没有一个确定性机制可以保证扭曲的比3美元更好, 没有随机化机制可以保证扭曲的比2美元更好。 没有随机化机制可以保证扭曲的比2美元更好。 目标在于设计一个机制来选择一个比2美元更短的人选。 但是, 这些更低的范围是Gkatzelis, Halpern, 和 Shah 都无法直接进入度机制的轮廓。 我们通过随机化机制可以保证扭曲比 $ $ = $ $ $ $ = $ $ $ $ 0. 04.96, 没有随机化机制可以保证扭曲更好提供 美元 美元 。 美元, rum ration ration ration ration rest ration ration ration ration ration rational delist ylation lexm lex lex m lex lex m lex lex m lex lex lex 。