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We study the problem of fairly allocating indivisible goods to groups of agents. Agents in the same group share the same set of goods even though they may have different preferences. Previous work has focused on unanimous fairness, in which…

Computer Science and Game Theory · Computer Science 2020-01-01 Erel Segal-Halevi , Warut Suksompong

An urban planner might design the spatial layout of transportation amenities so as to improve accessibility for underserved communities -- a fairness objective. However, implementing such a design might trigger processes of neighborhood…

Multiagent Systems · Computer Science 2024-02-12 J. Carlos Martínez Mori , Zhanzhan Zhao

Current methodologies in machine learning analyze the effects of various statistical parity notions of fairness primarily in light of their impacts on predictive accuracy and vendor utility loss. In this paper, we propose a new framework…

Machine Learning · Computer Science 2018-07-04 Lily Hu , Yiling Chen

This paper develops a model of in-kind redistribution where consumers participate in either a private market or a government-designed program, but not both. We characterize when a social planner, seeking to maximize weighted total surplus,…

General Economics · Economics 2024-10-25 Zi Yang Kang , Mitchell Watt

We introduce an end-to-end model of participatory budgeting grounded in social choice theory. This model accounts for both the first stage, in which participants propose projects to be shortlisted, and the second stage, in which they vote…

Computer Science and Game Theory · Computer Science 2023-09-07 Simon Rey , Ulle Endriss , Ronald de Haan

Classification algorithms are increasingly used in areas such as housing, credit, and law enforcement in order to make decisions affecting peoples' lives. These algorithms can change individual behavior deliberately (a fraud prediction…

Theoretical Economics · Economics 2023-07-06 Elizabeth Maggie Penn , John W. Patty

Partisan gerrymandering poses a threat to democracy. Moreover, the complexity of the districting task may exceed human capacities. One potential solution is using computational models to automate the districting process by optimizing…

Computers and Society · Computer Science 2020-06-30 Olivia Guest , Frank J. Kanayet , Bradley C. Love

In standard fair division models, we assume that all agents are selfish. However, in many scenarios, division of resources has a direct impact on the whole group or even society. Therefore, we study fair allocations of indivisible items…

Computer Science and Game Theory · Computer Science 2025-11-13 Argyris Deligkas , Eduard Eiben , Tiger-Lily Goldsmith , Dušan Knop , Šimon Schierreich

Sharing economy is a distributed peer-to-peer economic paradigm, which gives rise to a variety of social interactions for economic purposes. One fundamental distributed decision-making process is coalition formation for sharing certain…

Computer Science and Game Theory · Computer Science 2019-03-06 Chi-Kin Chau , Khaled Elbassioni

When selecting committees based on preferences of voters, a variety of different criteria can be considered. Two natural objectives are maximizing the utilitarian welfare (the sum of voters' utilities) and coverage (the number of…

Computer Science and Game Theory · Computer Science 2023-12-14 Markus Brill , Jannik Peters

Fairness in data-driven decision-making studies scenarios where individuals from certain population segments may be unfairly treated when being considered for loan or job applications, access to public resources, or other types of services.…

Databases · Computer Science 2022-10-19 Sina Shaham , Gabriel Ghinita , Cyrus Shahabi

Research on promoting cooperation among autonomous, self-regarding agents has often focused on the bi-objective optimisation problem: minimising the total incentive cost while maximising the frequency of cooperation. However, the optimal…

We consider a model where a subset of candidates must be selected based on voter preferences, subject to general constraints that specify which subsets are feasible. This model generalizes committee elections with diversity constraints,…

Computer Science and Game Theory · Computer Science 2026-02-10 Piotr Skowron

Now that machine learning algorithms lie at the center of many resource allocation pipelines, computer scientists have been unwittingly cast as partial social planners. Given this state of affairs, important questions follow. What is the…

Machine Learning · Computer Science 2019-05-02 Lily Hu , Yiling Chen

Multiwinner voting rules are used to select a small representative subset of candidates or items from a larger set given the preferences of voters. However, if candidates have sensitive attributes such as gender or ethnicity (when selecting…

Computers and Society · Computer Science 2018-06-20 L. Elisa Celis , Lingxiao Huang , Nisheeth K. Vishnoi

Gerrymandering, the deliberate manipulation of electoral district boundaries for political advantage, is a persistent issue in U.S. redistricting cycles. This paper introduces and analyzes a new phenomenon, 'votemandering'- a strategic…

Computer Science and Game Theory · Computer Science 2023-08-17 Sanyukta Deshpande , Ian G Ludden , Sheldon H Jacobson

We study proportional representation in the temporal voting model, where collective decisions are made repeatedly over time over a fixed horizon. Prior work has extensively investigated how proportional representation axioms from…

Computer Science and Game Theory · Computer Science 2026-05-13 Nicholas Teh

We consider the problem of fairly allocating indivisible public goods. We model the public goods as elements with feasibility constraints on what subsets of elements can be chosen, and assume that agents have additive utilities across…

Computer Science and Game Theory · Computer Science 2018-05-10 Brandon Fain , Kamesh Munagala , Nisarg Shah

The relationship of policy choice by majority voting and by maximization of utilitarian welfare has long been discussed. I consider choice between a status quo and a proposed policy when persons have interpersonally comparable cardinal…

Theoretical Economics · Economics 2024-12-30 Charles F. Manski

Conventional automated decision-support systems often prioritize predictive accuracy, overlooking the complexities of real-world settings where stakeholders' preferences may diverge or conflict. This can lead to outcomes that disadvantage…

Machine Learning · Computer Science 2025-11-25 Vittoria Vineis , Giuseppe Perelli , Gabriele Tolomei
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