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Metric Distortion Bounds for Randomized Social Choice
[article]
2021
arXiv
pre-print
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
arXiv:2111.03694v1
fatcat:trehtwiqcjf5jnmcwgjdg7ixkq