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Related papers: Metric Distortion under Group-Fair Objectives

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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 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…

Computer Science and Game Theory · Computer Science 2024-12-17 Alexandros A. Voudouris

We consider a social choice setting in which agents and alternatives are represented by points in a metric space, and the cost of an agent for an alternative is the distance between the corresponding points in the space. The goal is to…

Computer Science and Game Theory · Computer Science 2023-05-25 Elliot Anshelevich , Aris Filos-Ratsikas , Christopher Jerrett , Alexandros A. Voudouris

We consider the matching problem in the metric distortion framework. There are $n$ agents and $n$ items occupying points in a shared metric space, and the goal is to design a matching mechanism that outputs a low-cost matching between the…

Computer Science and Game Theory · Computer Science 2025-10-08 Jabari Hastings , Prasanna Ramakrishnan

We determine the quality of randomized social choice mechanisms in a setting in which the agents have metric preferences: every agent has a cost for each alternative, and these costs form a metric. We assume that these costs are unknown to…

Artificial Intelligence · Computer Science 2016-09-27 Elliot Anshelevich , John Postl

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 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…

Computer Science and Game Theory · Computer Science 2022-02-01 Ioannis Caragiannis , Nisarg Shah , Alexandros A. Voudouris

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

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 consider a setting with agents that have preferences over alternatives and are partitioned into disjoint districts. The goal is to choose one alternative as the winner using a mechanism which first decides a representative alternative…

Computer Science and Game Theory · Computer Science 2023-01-10 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

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

In most social choice settings, the participating agents express their preferences over the different alternatives in the form of linear orderings. While this clearly simplifies preference elicitation, it inevitably leads to poor…

Computer Science and Game Theory · Computer Science 2022-10-05 Georgios Amanatidis , Georgios Birmpas , Aris Filos-Ratsikas , Alexandros A. Voudouris

We study the distortion of one-sided and two-sided matching problems on the line. In the one-sided case, $n$ agents need to be matched to $n$ items, and each agent's cost in a matching is their distance from the item they were matched to.…

Computer Science and Game Theory · Computer Science 2025-02-04 Aris Filos-Ratsikas , Vasilis Gkatzelis , Mohamad Latifian , Emma Rewinski , Alexandros A. Voudouris

We consider the distributed single-winner metric voting problem on a line, where agents and alternative are represented by points on the line of real numbers, the agents are partitioned into disjoint districts, and the goal is to choose a…

Computer Science and Game Theory · Computer Science 2023-01-05 Alexandros A. Voudouris

Suppose that we have $n$ agents and $n$ items which lie in a shared metric space. We would like to match the agents to items such that the total distance from agents to their matched items is as small as possible. However, instead of having…

Computer Science and Game Theory · Computer Science 2023-05-23 Nima Anari , Moses Charikar , Prasanna Ramakrishnan

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 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

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 the problem of fair $k$-committee selection under an egalitarian objective. Given $n$ agents partitioned into $m$ groups (\eg, demographic quotas), the goal is to aggregate their preferences to form a committee of size $k$ that…

Data Structures and Algorithms · Computer Science 2026-01-01 Ameet Gadekar , Aristides Gionis , Suhas Thejaswi , Sijing Tu
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