On the Distortion of Single Winner Elections with Aligned Candidates
Pages 1409 - 1411
Abstract
We study the problem of selecting a single element from a set of candidates on which a group of agents has some spatial preferences. The exact distances between agent and candidate locations are unknown but we know how agents rank the candidates from the closest to the farthest. Whether it is desirable or undesirable, the winning candidate should either minimize or maximize its aggregate distance to the agents. The goal is to understand the optimal distortion, which evaluates how good an algorithm that determines the winner based only on the agent rankings performs against the optimal solution. We give a characterization of the distortion in the case of latent Euclidean distances such that the candidates are aligned, but the agent locations are not constrained. This setting generalizes the well-studied setting where both agents and candidates are located on the real line. Our bounds on the distortion are expressed with a parameter which relates, for every agent, the distance to her best candidate to the distance to any other alternative.
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- On the Distortion of Single Winner Elections with Aligned Candidates
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Published In
May 2023
3131 pages
ISBN:9781450394321
- General Chairs:
- Noa Agmon,
- Bo An,
- Program Chairs:
- Alessandro Ricci,
- William Yeoh
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Publisher
International Foundation for Autonomous Agents and Multiagent Systems
Richland, SC
Publication History
Published: 30 May 2023
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- Agence Nationale de la Recherche (ANR)
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AAMAS '23
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AAMAS '23: International Conference on Autonomous Agents and Multiagent Systems
May 29 - June 2, 2023
London, United Kingdom
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