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Related papers: Optimal Metric Distortion for Matching on the Line

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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 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

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

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

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 consider the one-sided matching problem, where n agents have preferences over n items, and these preferences are induced by underlying cardinal valuation functions. The goal is to match every agent to a single item so as to maximize the…

Computer Science and Game Theory · Computer Science 2020-09-15 Georgios Amanatidis , Georgios Birmpas , Aris Filos-Ratsikas , Alexandros A. Voudouris

We study matching settings in which a set of agents have private utilities over a set of items. Each agent reports a partition of the items into approval sets of different threshold utility levels. Given this limited information on input,…

Computer Science and Game Theory · Computer Science 2024-01-19 Mohamad Latifian , Alexandros A. Voudouris

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 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 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

We consider a voting problem in which a set of agents have metric preferences over a set of alternatives, and are also partitioned into disjoint groups. Given information about the preferences of the agents and their groups, our goal is to…

Computer Science and Game Theory · Computer Science 2024-04-23 Georgios Amanatidis , Elliot Anshelevich , Christopher Jerrett , 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

We study ordinal approximation algorithms for maximum-weight bipartite matchings. Such algorithms only know the ordinal preferences of the agents/nodes in the graph for their preferred matches, but must compete with fully omniscient…

Computer Science and Game Theory · Computer Science 2017-07-07 Elliot Anshelevich , Wennan Zhu

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

In a setting where $m$ items need to be partitioned among $n$ agents, we evaluate the performance of mechanisms that take as input each agent's \emph{ordinal preferences}, i.e., their ranking of the items from most- to least-preferred. The…

Computer Science and Game Theory · Computer Science 2026-02-13 Ioannis Caragiannis , Vasilis Gkatzelis , Sebastian Homrighausen

In this work we consider general facility location and social choice problems, in which sets of agents $\mathcal{A}$ and facilities $\mathcal{F}$ are located in a metric space, and our goal is to assign agents to facilities (as well as…

Multiagent Systems · Computer Science 2018-05-09 Elliot Anshelevich , Wennan Zhu

We initiate the study of distortion in stable matching. Concretely, we aim to design algorithms that have limited access to the agents' cardinal preferences and compute stable matchings of high quality with respect to some aggregate…

Computer Science and Game Theory · Computer Science 2026-02-17 Aris Filos-Ratsikas , Georgios Kalantzis

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

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
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