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Related papers: The Metric Distortion of Multiwinner Voting

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We study the problem of selecting a representative committee of $k$ agents from a collection of $n$ agents in a common metric space. This problem is related to choosing $k$ facilities in facility location and $k$-median problems. However,…

Computer Science and Game Theory · Computer Science 2025-10-27 Christopher Jerrett , Elliot Anshelevich

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

We introduce the notion of {\em Distance Restricted Manipulation}, where colluding manipulator(s) need to compute if there exist votes which make their preferred alternative win the election when their knowledge about the others' votes is a…

Computer Science and Game Theory · Computer Science 2020-11-30 Aditya Anand , Palash Dey

We study multiwinner elections with approval-based preferences. An instance of a multiwinner election consists of a set of alternatives, a population of voters---each voter approves a subset of alternatives, and the desired committee size…

Computer Science and Game Theory · Computer Science 2019-10-15 Piotr Skowron

We introduce a novel definition for a small set R of k points being "representative" of a larger set in a metric space. Given a set V (e.g., documents or voters) to represent, and a set C of possible representatives, our criterion requires…

Computer Science and Game Theory · Computer Science 2024-01-25 Yusuf Hakan Kalayci , David Kempe , Vikram Kher

Multi-winner approval-based voting has received considerable attention recently. A voting rule in this setting takes as input ballots in which each agent approves a subset of the available alternatives and outputs a committee of…

Computer Science and Game Theory · Computer Science 2024-02-15 Ioannis Caragiannis , Rob LeGrand , Evangelos Markakis , Emmanouil Pountourakis

Motivated by recent work in computational social choice, we extend the metric distortion framework to clustering problems. Given a set of $n$ agents located in an underlying metric space, our goal is to partition them into $k$ clusters,…

Computer Science and Game Theory · Computer Science 2024-02-07 Jakob Burkhardt , Ioannis Caragiannis , Karl Fehrs , Matteo Russo , Chris Schwiegelshohn , Sudarshan Shyam

We study the following multiagent variant of the knapsack problem. We are given a set of items, a set of voters, and a value of the budget; each item is endowed with a cost and each voter assigns to each item a certain value. The goal is to…

Computer Science and Game Theory · Computer Science 2018-11-14 Till Fluschnik , Piotr Skowron , Mervin Triphaus , Kai Wilker

Mechanism design is concerned with settings where a policymaker (or social planner) faces the problem of aggregating the announced preferences of multiple agents into a collective (or social), system-wide decision. One of the most important…

Multiagent Systems · Computer Science 2020-03-02 Mohammad Ali Javidian , Pooyan Jamshidi , Marco Valtorta , Rasoul Ramezanian

In the impartial selection problem, a subset of agents up to a fixed size $k$ among a group of $n$ is to be chosen based on votes cast by the agents themselves. A selection mechanism is impartial if no agent can influence its own chance of…

Computer Science and Game Theory · Computer Science 2024-08-06 Javier Cembrano , Svenja M. Griesbach , Maximilian J. Stahlberg

We study a model of proxy voting where the candidates, voters, and proxies are all located on the real line, and instead of voting directly, each voter delegates its vote to the closest proxy. The goal is to find a set of proxies that is…

Computer Science and Game Theory · Computer Science 2020-12-15 Elliot Anshelevich , Zack Fitzsimmons , Rohit Vaish , Lirong Xia

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

The notion of distortion in social choice problems has been defined to measure the loss in efficiency -- typically measured by the utilitarian social welfare, the sum of utilities of the participating agents -- due to having access only to…

Computer Science and Game Theory · Computer Science 2021-03-02 Elliot Anshelevich , Aris Filos-Ratsikas , Nisarg Shah , Alexandros A. Voudouris

There has been much recent work on multiwinner voting systems. However, sometimes a committee is highly structured, and if we want to vote for such a committee, our voting method should be more structured as well. We consider committees…

Computer Science and Game Theory · Computer Science 2022-11-14 Karl-Dieter Crisman

The study of fairness in multiwinner elections focuses on settings where candidates have attributes. However, voters may also be divided into predefined populations under one or more attributes (e.g., "California" and "Illinois" populations…

Computer Science and Game Theory · Computer Science 2022-11-24 Kunal Relia

In many real world situations, collective decisions are made using voting. Moreover, scenarios such as committee or board elections require voting rules that return multiple winners. In multi-winner approval voting (AV), an agent may vote…

Computer Science and Game Theory · Computer Science 2019-05-31 Jaelle Scheuerman , Jason L. Harman , Nicholas Mattei , K. Brent Venable

We study the problem of selection in the context of Bayesian persuasion. We are given multiple agents with hidden values (or quality scores), to whom resources must be allocated by a welfare-maximizing decision-maker. An intermediary with…

Computer Science and Game Theory · Computer Science 2025-11-18 Yannan Bai , Kamesh Munagala , Yiheng Shen , Davidson Zhu

Classical work on metric space based committee selection problem interprets distance as ``near is better''. In this work, motivated by real-life situations, we interpret distance as ``far is better''. Formally stated, we initiate the study…

Data Structures and Algorithms · Computer Science 2024-05-27 Sushmita Gupta , Tanmay Inamdar , Pallavi Jain , Daniel Lokshtanov , Fahad Panolan , Saket Saurabh

Purpose: Multiwinner voting rules typically require full knowledge of voter preferences, which becomes impractical in large-scale or attention-limited settings. This paper investigates how accurately a winning committee can be approximated…

Computer Science and Game Theory · Computer Science 2026-04-01 Itay Asher Zimet , Shiri Alouf-Heffetz , Nimrod Talmon

We consider multiwinner elections in Euclidean space using the minimax Chamberlin-Courant rule. In this setting, voters and candidates are embedded in a $d$-dimensional Euclidean space, and the goal is to choose a committee of $k$…

Computer Science and Game Theory · Computer Science 2022-05-30 Chinmay Sonar , Subhash Suri , Jie Xue