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When scheduling public works or events in a shared facility one needs to accommodate preferences of a population. We formalize this problem by introducing the notion of a collective schedule. We show how to extend fundamental tools from…

Computer Science and Game Theory · Computer Science 2018-03-21 Fanny Pascual , Krzysztof Rzadca , Piotr Skowron

Ranking models are typically designed to provide rankings that optimize some measure of immediate utility to the users. As a result, they have been unable to anticipate an increasing number of undesirable long-term consequences of their…

Machine Learning · Computer Science 2019-05-15 Behzad Tabibian , Vicenç Gómez , Abir De , Bernhard Schölkopf , Manuel Gomez Rodriguez

We are studying long term sequence prediction (forecasting). We approach this by investigating criteria for choosing a compact useful state representation. The state is supposed to summarize useful information from the history. We want a…

Machine Learning · Computer Science 2012-02-10 Peter Sunehag , Marcus Hutter

Cumulative prospect theory (CPT) is the first theory for decision-making under uncertainty that combines full theoretical soundness and empirically realistic features [P.P. Wakker - Prospect theory: For risk and ambiguity, Page 2]. While…

Logic in Computer Science · Computer Science 2025-05-15 Thomas Brihaye , Krishnendu Chatterjee , Stefanie Mohr , Maximilian Weininger

We consider a voting model, where a number of candidates need to be selected subject to certain feasibility constraints. The model generalises committee elections (where there is a single constraint on the number of candidates that need to…

Computer Science and Game Theory · Computer Science 2025-09-24 Tomáš Masařík , Grzegorz Pierczyński , Piotr Skowron

It has recently been shown that if feedback effects of decisions are ignored, then imposing fairness constraints such as demographic parity or equality of opportunity can actually exacerbate unfairness. We propose to address this challenge…

Machine Learning · Computer Science 2021-10-12 Min Wen , Osbert Bastani , Ufuk Topcu

In this work, we consider a cooperative multi-agent Markov decision process (MDP) involving m agents. At each decision epoch, all the m agents independently select actions in order to maximize a common long-term objective. In the policy…

Machine Learning · Computer Science 2024-05-01 Lakshmi Mandal , Chandrashekar Lakshminarayanan , Shalabh Bhatnagar

Committee-selection problems arise in many contexts and applications, and there has been increasing interest within the social choice research community on identifying which properties are satisfied by different multi-winner voting rules.…

Artificial Intelligence · Computer Science 2025-08-11 Joshua Caiata , Ben Armstrong , Kate Larson

Human-robot interaction exerts influence towards the human, which often changes behavior. This article explores an externality of this changed behavior - preference change. It expands on previous work on preference change in AI systems.…

Robotics · Computer Science 2022-06-22 Matija Franklin , Hal Ashton

Humans have come to rely on machines for reducing excessive information to manageable representations. But this reliance can be abused -- strategic machines might craft representations that manipulate their users. How can a user make good…

Machine Learning · Computer Science 2022-06-20 Vineet Nair , Ganesh Ghalme , Inbal Talgam-Cohen , Nir Rosenfeld

A multicriteria group choice problem is considered in the paper. The model includes a set of feasible alternatives, a vector criterion, and n preference relations of the decision makers (DMs). Each preference relation is a cone relation…

Optimization and Control · Mathematics 2019-05-14 Alexey O. Zakharov

We study a social choice setting of manipulation in elections and extend the usual model in two major ways: first, instead of considering a single manipulating agent, in our setting there are several, possibly competing ones; second,…

Multiagent Systems · Computer Science 2020-05-12 Martin Koutecký , Nimrod Talmon

This paper proposes to use probabilistic model checking to synthesize optimal robot policies in multi-tasking autonomous systems that are subject to human-robot interaction. Given the convincing empirical evidence that human behavior can be…

Artificial Intelligence · Computer Science 2016-11-01 Sebastian Junges , Nils Jansen , Joost-Pieter Katoen , Ufuk Topcu

For a society to remain healthy and prosperous, people must collectively behave and act to contribute to the common good, even if there is often a tradeoff against their individual benefit. Paradigmatic examples include the adoption of…

Systems and Control · Electrical Eng. & Systems 2026-05-05 Mengbin Ye , Lorenzo Zino , Ming Cao

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

Random utility theory models an agent's preferences on alternatives by drawing a real-valued score on each alternative (typically independently) from a parameterized distribution, and then ranking the alternatives according to scores. A…

Multiagent Systems · Computer Science 2012-11-13 Hossein Azari Soufiani , David C. Parkes , Lirong Xia

This paper investigates the optimization problem of an infinite stage discrete time Markov decision process (MDP) with a long-run average metric considering both mean and variance of rewards together. Such performance metric is important…

Optimization and Control · Mathematics 2020-08-11 Li Xia

Iterative voting is a natural model of repeated strategic decision-making in social choice theory when agents have the opportunity to update their votes prior to finalizing the group decision. Prior work has analyzed the efficacy of…

Computer Science and Game Theory · Computer Science 2025-06-12 Joshua Kavner , Lirong Xia

We introduce a logic specifically designed to support reasoning about social choice functions. The logic includes operators to capture strategic ability, and operators to capture agent preferences. We establish a correspondence between…

Multiagent Systems · Computer Science 2011-04-29 Nicolas Troquard , Wiebe van der Hoek , Michael Wooldridge

The goal of this paper is to provide mathematically rigorous tools for modelling the evolution of a community of interacting individuals. We model the population by a measure space where the measure determines the abundance of individual…

Probability · Mathematics 2017-05-17 Thomas Cass , Terry Lyons