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The theory of two-sided matching has been extensively developed and applied to many real-life application domains. As the theory has been applied to increasingly diverse types of environments, researchers and practitioners have encountered…

Computer Science and Game Theory · Computer Science 2024-09-25 Kei Kimura , Kwei-guu Liu , Zhaohong Sun , Kentaro Yahiro , Makoto Yokoo

We study a fair resource sharing problem, where a set of resources are to be shared among a group of agents. Each agent demands one resource and each resource can serve a limited number of agents. An agent cares about what resource they get…

Computer Science and Game Theory · Computer Science 2023-07-14 Jiarui Gan , Bo Li , Yingkai Li

The classic Gibbard-Satterthwaite theorem says that every strategy-proof voting rule with at least three possible candidates must be dictatorial. In \cite{McL11}, McLennan showed that a similar impossibility result holds even if we consider…

Computer Science and Game Theory · Computer Science 2015-04-13 Samantha Leung , Edward Lui , Rafael Pass

Autonomous systems are increasingly expected to operate in the presence of adversaries, though adversaries may infer sensitive information simply by observing a system. Therefore, present a deceptive sequential decision-making framework…

Modeling the preferences of agents over a set of alternatives is a principal concern in many areas. The dominant approach has been to find a single reward/utility function with the property that alternatives yielding higher rewards are…

Machine Learning · Computer Science 2022-06-09 Alihan Hüyük , William R. Zame , Mihaela van der Schaar

Social decision schemes (SDSs) map the ordinal preferences of individual voters over multiple alternatives to a probability distribution over the alternatives. In order to study the axiomatic properties of SDSs, we lift preferences over…

Computer Science and Game Theory · Computer Science 2024-08-27 Felix Brandt , Patrick Lederer , Warut Suksompong

We study the trade-off between envy and inefficiency in repeated resource allocation settings with stochastic replenishments, motivated by real-world systems such as food banks and medical supply chains. Specifically, we consider a model in…

Optimization and Control · Mathematics 2025-09-01 Chido Onyeze , Sean R. Sinclair , Chamsi Hssaine , Siddhartha Banerjee

We consider a multi-agent resource allocation setting that models the assignment of papers to reviewers. A recurring issue in allocation problems is the compatibility of welfare/efficiency and fairness. Given an oracle to find a…

Computer Science and Game Theory · Computer Science 2019-08-02 Haris Aziz , Xin Huang , Nicholas Mattei , Erel Segal-Halevi

We consider Pareto-optimal matchings (POMs) in a many-to-many market of applicants and courses where applicants have preferences, which may include ties, over individual courses and lexicographic preferences over sets of courses. Since this…

Computer Science and Game Theory · Computer Science 2015-12-07 Katarína Cechlárová , Pavlos Eirinakis , Tamás Fleiner , Dimitrios Magos , David Manlove , Ioannis Mourtos , Eva Oceláková , Baharak Rastegari

When allocating indivisible resources or tasks, an envy-free allocation or equitable allocation may not exist. We present a sufficient condition and an algorithm to achieve envy-freeness and equitability when monetary transfers are allowed.…

Computer Science and Game Theory · Computer Science 2020-03-19 Haris Aziz

Misaligned artificial agents might resist shutdown. One proposed solution is to train agents to lack preferences between different-length trajectories. The Discounted Reward for Same-Length Trajectories (DReST) reward function does this by…

Artificial Intelligence · Computer Science 2026-05-13 Carissa Cullen , Harry Garland , Alexander Roman , Louis Thomson , Christos Ziakas , Elliott Thornley

In fair division of indivisible goods, using sequences of sincere choices (or picking sequences) is a natural way to allocate the objects. The idea is the following: at each stage, a designated agent picks one object among those that…

Computer Science and Game Theory · Computer Science 2016-04-07 Sylvain Bouveret , Michel Lemaître

We study and provide efficient algorithms for multi-objective model checking problems for Markov Decision Processes (MDPs). Given an MDP, M, and given multiple linear-time (\omega -regular or LTL) properties \varphi\_i, and probabilities…

Logic in Computer Science · Computer Science 2015-07-01 Kousha Etessami , Marta Kwiatkowska , Moshe Y. Vardi , Mihalis Yannakakis

We consider K-Facility Location games, where n strategic agents report their locations in a metric space, and a mechanism maps them to K facilities. Our main result is an elegant characterization of deterministic strategyproof mechanisms…

Computer Science and Game Theory · Computer Science 2012-07-05 Dimitris Fotakis , Christos Tzamos

In many-server systems it is crucial to staff the right number of servers so that targeted service levels are met. These staffing problems typically lead to constraint satisfaction problems that are hard to solve. During the last decade, a…

Probability · Mathematics 2014-01-30 A. J. E. M. Janssen , Johan S. H. van Leeuwaarden

Stochastic dominance is a preference relation of uncertain prospect defined over a class of utility functions. While this utility class represents basic properties of risk aversion, it includes some extreme utility functions rarely…

Optimization and Control · Mathematics 2015-12-29 Jian Hu , Gevorg Stepanyan

We consider the discrete assignment problem in which agents express ordinal preferences over objects and these objects are allocated to the agents in a fair manner. We use the stochastic dominance relation between fractional or randomized…

Computer Science and Game Theory · Computer Science 2015-06-18 Haris Aziz , Serge Gaspers , Simon Mackenzie , Toby Walsh

The Gibbard-Satterthwaite Impossibility Theorem holds that dictatorship is the only Pareto optimal and strategyproof social choice function on the full domain of preferences. Much of the work in mechanism design aims at getting around this…

Computer Science and Game Theory · Computer Science 2017-03-21 Sophie Bade , Yannai A. Gonczarowski

This paper studies the robustness of reinforcement learning algorithms to errors in the learning process. Specifically, we revisit the benchmark problem of discrete-time linear quadratic regulation (LQR) and study the long-standing open…

Optimization and Control · Mathematics 2021-03-16 Bo Pang , Zhong-Ping Jiang

This paper studies a dynamic discrete-time queuing model where at every period players get a new job and must send all their jobs to a queue that has a limited capacity. Players have an incentive to send their jobs as late as possible;…

Computer Science and Game Theory · Computer Science 2023-02-08 Lucas Baudin , Marco Scarsini , Xavier Venel
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