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In the well-studied metric distortion problem in social choice, we have voters and candidates located in a shared metric space, and the objective is to design a voting rule that selects a candidate with minimal total distance to the voters.…

Computer Science and Game Theory · Computer Science 2025-05-21 Moses Charikar , Prasanna Ramakrishnan , Zihan Tan , Kangning Wang

We consider the following well-studied problem of metric distortion in social choice. Suppose we have an election with $n$ voters and $m$ candidates located in a shared metric space. We would like to design a voting rule that chooses a…

Computer Science and Game Theory · Computer Science 2024-11-07 Moses Charikar , Prasanna Ramakrishnan , Kangning Wang , Hongxun Wu

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

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…

Computer Science and Game Theory · Computer Science 2021-11-09 Moses Charikar , Prasanna Ramakrishnan

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

In the metric distortion problem, a set of voters and candidates lie in a common metric space, and a committee of $k$ candidates must be elected. The objective is to minimize a social cost, defined as a function of the distances between…

Computer Science and Game Theory · Computer Science 2025-10-16 Javier Cembrano , Golnoosh Shahkarami

We study deliberative social choice, where voters engage in small-group discussions to output collective preferences that are then aggregated by a social choice rule. We introduce a simple deliberation-via-matching protocol. In this…

Computer Science and Game Theory · Computer Science 2026-04-27 Kamesh Munagala , Qilin Ye , Ian Zhang

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

Selecting representatives based on voters' preferences is a fundamental problem in social choice theory. While cardinal utility functions offer a detailed representation of preferences, ordinal rankings are often the only available…

Computer Science and Game Theory · Computer Science 2024-12-17 Kiarash Banihashem , Diptarka Chakraborty , Shayan Chashm Jahan , Iman Gholami , MohammadTaghi Hajiaghayi , Mohammad Mahdavi , Max Springer

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

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

We develop new voting mechanisms for the case when voters and candidates are located in an arbitrary unknown metric space, and the goal is to choose a candidate minimizing social cost: the total distance from the voters to this candidate.…

Artificial Intelligence · Computer Science 2019-06-26 Ben Abramowitz , Elliot Anshelevich , Wennan Zhu

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

We study the following metric distortion problem: there are two finite sets of points, $V$ and $C$, that lie in the same metric space, and our goal is to choose a point in $C$ whose total distance from the points in $V$ is as small as…

Computer Science and Game Theory · Computer Science 2020-09-08 Vasilis Gkatzelis , Daniel Halpern , Nisarg Shah

The metric distortion of a randomized social choice function (RSCF) quantifies its worst-case approximation ratio to the optimal social cost when the voters' costs for alternatives are given by distances in a metric space. This notion has…

Computer Science and Game Theory · Computer Science 2025-02-13 Fabian Frank , Patrick Lederer

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

We consider models for social choice where voters rank a set of choices (or alternatives) by deliberating in small groups of size at most $k$, and these outcomes are aggregated by a social choice rule to find the winning alternative. We…

Computer Science and Game Theory · Computer Science 2025-03-21 Ashish Goel , Mohak Goyal , Kamesh Munagala

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 consider a social choice setting with agents that are partitioned into disjoint groups, and have metric preferences over a set of alternatives. Our goal is to choose a single alternative aiming to optimize various objectives that are…

Computer Science and Game Theory · Computer Science 2021-07-13 Elliot Anshelevich , Aris Filos-Ratsikas , Alexandros A. Voudouris

We provide mechanisms and new metric distortion bounds for line-up elections. In such elections, a set of $n$ voters, $m$ candidates, and $\ell$ positions are all located in a metric space. The goal is to choose a set of candidates and…

Computer Science and Game Theory · Computer Science 2025-02-25 Christopher Jerrett , Yue Han , Elliot Anshelevich
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