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Related papers: Utilitarian Distortion Under Probabilistic Voting

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Metric distortion in social choice is a framework for evaluating how well voting rules minimize social cost when both voters and candidates exist in a shared metric space, with a voter's cost defined by their distance to a candidate. Voters…

Computer Science and Game Theory · Computer Science 2025-02-14 Mohak Goyal , Sahasrajit Sarmasarkar

A voting rule decides on a probability distribution over a set of m alternatives, based on rankings of those alternatives provided by agents. We assume that agents have cardinal utility functions over the alternatives, but voting rules have…

Computer Science and Game Theory · Computer Science 2024-01-23 Soroush Ebadian , Anson Kahng , Dominik Peters , Nisarg Shah

Distortion-based analysis has established itself as a fruitful framework for comparing voting mechanisms. m voters and n candidates are jointly embedded in an (unknown) metric space, and the voters submit rankings of candidates by…

Computer Science and Game Theory · Computer Science 2019-12-17 David Kempe

Social choice theory offers a wealth of approaches for selecting a candidate on behalf of voters based on their reported preference rankings over options. When voters have underlying utilities for these options, however, using preference…

Computer Science and Game Theory · Computer Science 2025-10-24 Luise Ge , Gregory Kehne , Yevgeniy Vorobeychik

We study social choice rules under the utilitarian distortion framework, with an additional metric assumption on the agents' costs over the alternatives. In this approach, these costs are given by an underlying metric on the set of all…

Computer Science and Game Theory · Computer Science 2021-01-15 Ashish Goel , Anilesh Kollagunta Krishnaswamy , Kamesh Munagala

We consider elections where both voters and candidates can be associated with points in a metric space and voters prefer candidates that are closer to those that are farther away. It is often assumed that the optimal candidate is the one…

Computer Science and Game Theory · Computer Science 2019-01-23 Grzegorz Pierczyński , Piotr Skowron

One way of evaluating social choice (voting) rules is through a utilitarian distortion framework. In this model, we assume that agents submit full rankings over the alternatives, and these rankings are generated from underlying, but…

Computer Science and Game Theory · Computer Science 2018-10-03 Ashish Goel , Reyna Hulett , Anilesh K. Krishnaswamy

In distortion-based analysis of social choice rules over metric spaces, one assumes that all voters and candidates are jointly embedded in a common metric space. Voters rank candidates by non-decreasing distance. The mechanism, receiving…

Computer Science and Game Theory · Computer Science 2019-11-21 David Kempe

In this work we study the metric distortion problem in voting theory under a limited amount of ordinal information. Our primary contribution is threefold. First, we consider mechanisms which perform a sequence of pairwise comparisons…

Computer Science and Game Theory · Computer Science 2021-07-07 Ioannis Anagnostides , Dimitris Fotakis , Panagiotis Patsilinakos

The metric distortion framework posits that n voters and m candidates are jointly embedded in a metric space such that voters rank candidates that are closer to them higher. A voting rule's purpose is to pick a candidate with minimum total…

Computer Science and Game Theory · Computer Science 2023-07-03 Fatih Erdem Kizilkaya , David Kempe

{\em Distortion} is a well-established notion for quantifying the loss of social welfare that may occur in voting. As voting rules take as input only ordinal information, they are essentially forced to neglect the exact values the agents…

Computer Science and Game Theory · Computer Science 2024-10-15 Ioannis Caragiannis , Karl Fehrs

We study the utilitarian distortion of social choice mechanisms under the recently proposed learning-augmented framework where some (possibly unreliable) predicted information about the preferences of the agents is given as input. In…

Computer Science and Game Theory · Computer Science 2025-02-11 Aris Filos-Ratsikas , Georgios Kalantzis , Alexandros A. Voudouris

We study the problem of designing voting rules that take as input the ordinal preferences of $n$ agents over a set of $m$ alternatives and output a single alternative, aiming to optimize the overall happiness of the agents. The input to the…

Computer Science and Game Theory · Computer Science 2023-06-01 Vasilis Gkatzelis , Mohamad Latifian , Nisarg Shah

We study the problem of minimizing metric distortion in multi-winner elections, where a committee of size $k$ is selected from a set of candidates based on voters' ordinal preferences. We assume that voters and candidates are embedded on a…

Computer Science and Game Theory · Computer Science 2026-02-18 Negar Babashah , Hasti Karimi , Masoud Seddighin , Golnoosh Shahkarami

We conjecture that Borda count is the ranked choice voting method that best preserves the outcome of an election with randomly corrupted votes, among all fair voting methods with small influences satisfying the Condorcet Loser Criterion.…

Computer Science and Game Theory · Computer Science 2022-09-23 Steven Heilman

It is well known, by the Gibbard-Satterthwaite Theorem, that when there are more than two candidates, any non-dictatorial voting rule can be manipulated by untruthful voters. But how strong is the incentive to manipulate under different…

Computer Science and Game Theory · Computer Science 2026-02-27 Ratip Emin Berker , Vincent Conitzer , Eden Hartman , Jiayuan Liu , Caspar Oesterheld

We study positional voting rules when candidates and voters are embedded in a common metric space, and cardinal preferences are naturally given by distances in the metric space. In a positional voting rule, each candidate receives a score…

Computer Science and Game Theory · Computer Science 2017-11-22 Yu Cheng , Shaddin Dughmi , David Kempe

We view voting rules as classifiers that assign a winner (a class) to a profile of voters' preferences (an instance). We propose to apply techniques from formal explainability, most notably abductive and contrastive explanations, to…

Artificial Intelligence · Computer Science 2024-08-27 Clément Contet , Umberto Grandi , Jérôme Mengin

We study the design of voting rules in the metric distortion framework. It is known that any deterministic rule suffers distortion of at least $3$, and that randomized rules can achieve distortion strictly less than $3$, often at the cost…

Computer Science and Game Theory · Computer Science 2026-02-10 Ziyi Cai , D. D. Gao , Prasanna Ramakrishnan , Kangning Wang

We study higher statistical moments of Distortion for randomized social choice in a metric implicit utilitarian model. The Distortion of a social choice mechanism is the expected approximation factor with respect to the optimal utilitarian…

Computer Science and Game Theory · Computer Science 2020-04-29 Brandon Fain , William Fan , Kamesh Munagala
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