Metric distortion of obnoxious distributed voting

We consider a distributed voting problem with a set of agents that are partitioned into disjoint groups and a set of obnoxious alternatives. Agents and alternatives are represented by points in a metric space. The goal is to compute the alternative that maximizes the total distance from all agents using a two-step mechanism which, given some information about the distances between agents and alternatives, first chooses a representative alternative for each group of agents, and then declares one of them as the overall winner. Due to the restricted nature of the mechanism and the potentially limited information it has to make its decision, it might not be always possible to choose the optimal alternative. We show tight bounds on the distortion of different mechanisms depending on the amount of the information they have access to; in particular, we study full-information and ordinal mechanisms. • We study a metric distributed voting model in which agents have metric preferences over obnoxious alternatives. • The agents are partitioned into groups, and decisions are made via two-step mechanisms. • We show tight bounds on the distortion of deterministic full-information and ordinal mechanisms.