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This paper presents some fundamental collective choice theory for information system designers, particularly those working in the field of computer-supported cooperative work. This paper is focused on a presentation of Arrow's Possibility…

Multiagent Systems · Computer Science 2007-05-23 Walter Eaves

As recommender systems are being designed and deployed for an increasing number of socially-consequential applications, it has become important to consider what properties of fairness these systems exhibit. There has been considerable…

Information Retrieval · Computer Science 2020-09-08 Nasim Sonboli , Robin Burke , Nicholas Mattei , Farzad Eskandanian , Tian Gao

Multi-winner voting is the process of selecting a fixed-size set of representative candidates based on voters' preferences. It occurs in applications ranging from politics (parliamentary elections) to the design of modern computer…

Computer Science and Game Theory · Computer Science 2022-11-22 Martin Lackner , Piotr Skowron

This paper introduces Propose or Vote (PoV), a democratic procedure for collective decision-making and elections that does not rely on a central mechanism designer. In the first stage, members of a polity choose whether to become…

Theoretical Economics · Economics 2025-12-23 Hans Gersbach

Arrow's `impossibility' theorem asserts that there are no satisfactory methods of aggregating individual preferences into collective preferences in many complex situations. This result has ramifications in economics, politics, i.e., the…

Theoretical Economics · Economics 2019-09-18 T. Erber , M. J. Frank

In this paper, we present a link between preference-based and multiobjective sequential decision-making. While transforming a multiobjective problem to a preference-based one is quite natural, the other direction is a bit less obvious. We…

Artificial Intelligence · Computer Science 2017-01-04 Paul Weng

Online social networks are used to diffuse opinions and ideas among users, enabling a faster communication and a wider audience. The way in which opinions are conditioned by social interactions is usually called social influence. Social…

Social and Information Networks · Computer Science 2019-07-03 Federico Corò , Emilio Cruciani , Gianlorenzo D'Angelo , Stefano Ponziani

It is well known that no reasonable voting rule is strategyproof. Moreover, the common Plurality rule is particularly prone to strategic behavior of the voters and empirical studies show that people often vote strategically in practice.…

Computer Science and Game Theory · Computer Science 2014-04-22 Reshef Meir , Omer Lev , Jeffrey S. Rosenschein

The influence of additional information on the decision making of agents, who are interacting members of a society, is analyzed within the mathematical framework based on the use of quantum probabilities. The introduction of social…

Physics and Society · Physics 2015-10-14 V. I. Yukalov , D. Sornette

Egalitarian considerations play a central role in many areas of social choice theory. Applications of egalitarian principles range from ensuring everyone gets an equal share of a cake when deciding how to divide it, to guaranteeing balance…

Artificial Intelligence · Computer Science 2021-03-10 Sirin Botan , Ronald de Haan , Marija Slavkovik , Zoi Terzopoulou

Despite extensive theoretical research on proportionality in approval-based multiwinner voting, its impact on which committees and candidates can be selected in practice remains poorly understood. We address this gap by (i) analyzing the…

Computer Science and Game Theory · Computer Science 2025-11-13 Niclas Boehmer , Lara Glessen , Jannik Peters

Algorithmic fairness in the context of personalized recommendation presents significantly different challenges to those commonly encountered in classification tasks. Researchers studying classification have generally considered fairness to…

Artificial Intelligence · Computer Science 2024-02-28 Amanda Aird , Paresha Farastu , Joshua Sun , Elena Štefancová , Cassidy All , Amy Voida , Nicholas Mattei , Robin Burke

With the growing adoption of AI systems, reasoning about how society can exert control over AI becomes an increasingly urgent problem. Existing work on democratic control largely focuses on macro-level governance. In contrast, we propose a…

Computers and Society · Computer Science 2026-05-19 Paul Anton Bachmann , Niclas Boehmer , Lukas Daniel Klausner , Martin Lackner

Based on the observation that many existing discrete choice models admit a welfare function of utilities whose gradient gives the choice probability vector, we propose a new representation of discrete choice model which we call the…

Optimization and Control · Mathematics 2015-03-09 Guiyun Feng , Xiaobo Li , Zizhuo Wang

Standard methods in preference learning involve estimating the parameters of discrete choice models from data of selections (choices) made by individuals from a discrete set of alternatives (the choice set). While there are many models for…

Machine Learning · Computer Science 2021-08-18 Kiran Tomlinson , Johan Ugander , Austin R. Benson

Learning-based approaches, such as reinforcement and imitation learning are gaining popularity in decision-making for autonomous driving. However, learned policies often fail to generalize and cannot handle novel situations well. Asking and…

Machine Learning · Computer Science 2020-11-13 Patrick Hart , Alois Knoll

We study three axioms in the model of constrained social choice under uncertainty where (i) agents have subjective expected utility preferences over acts and (ii) different states of nature have (possibly) different sets of available…

Theoretical Economics · Economics 2024-08-05 Eric Bahel

A key promise of democratic voting is that, by accounting for all constituents' preferences, it produces decisions that benefit the constituency overall. It is alarming, then, that all deterministic voting rules have unbounded distortion:…

Computer Science and Game Theory · Computer Science 2023-05-22 Bailey Flanigan , Ariel D. Procaccia , Sven Wang

Sequential decision-making is desired to align with human intents and exhibit versatility across various tasks. Previous methods formulate it as a conditional generation process, utilizing return-conditioned diffusion models to directly…

Machine Learning · Computer Science 2024-10-11 Xudong Yu , Chenjia Bai , Haoran He , Changhong Wang , Xuelong Li

An important -- but very demanding -- property in collective decision-making is strategyproofness, which requires that voters cannot benefit from submitting insincere preferences. Gibbard (1977) has shown that only rather unattractive rules…

Computer Science and Game Theory · Computer Science 2024-12-17 Felix Brandt , Patrick Lederer