The Metric Distortion of Multiwinner Voting

The Metric Distortion of Multiwinner Voting
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多方投票的指标扭曲

DOI:
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发表时间:
2022
期刊:
AAAI Conference on Artificial Intelligence
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通讯作者:
Alexandros A. Voudouris
Alexandros A. Voudouris
中科院分区:
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文献类型:
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作者:
I. Caragiannis;Nisarg Shah;Alexandros A. Voudouris

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We extend the recently introduced framework of metric distortion to multiwinner voting. In this framework, n agents and m alternatives are located in an underlying metric space. The exact distances between agents and alternatives are unknown. Instead, each agent provides a ranking of the alternatives, ordered from the closest to the farthest. Typically, the goal is to select a single alternative that approximately minimizes the total distance from the agents, and the worst-case approximation ratio is termed distortion. In the case of multiwinner voting, the goal is to select a committee of k alternatives that (approximately) minimizes the total cost to all agents. We consider the scenario where the cost of an agent for a committee is her distance from the q-th closest alternative in the committee. We reveal a surprising trichotomy on the distortion of multiwinner voting rules in terms of k and q: The distortion is unbounded when q
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