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The study of learning in games typically assumes that each player always has access to all of their actions. However, in many practical scenarios, players' available actions might be restricted due to exogenous stochasticity. To model this…

Computer Science and Game Theory · Computer Science 2026-05-12 Thomas Schwarz , Ryann Sim , Chun Kai Ling

In this paper we present a novel generic mapping between Graphical Games and Markov Random Fields so that pure Nash equilibria in the former can be found by statistical inference on the latter. Thus, the problem of deciding whether a…

Computer Science and Game Theory · Computer Science 2007-05-23 Constantinos Daskalakis

In this paper, we solve the problem of learning a generalized Nash equilibrium (GNE) in merely monotone games. First, we propose a novel continuous semi-decentralized solution algorithm without projections that uses first-order information…

Systems and Control · Electrical Eng. & Systems 2021-10-07 Suad Krilašević , Sergio Grammatico

The Nash equilibrium is an important benchmark for behaviour in systems of strategic autonomous agents. Polymatrix games are a succinct and expressive representation of multiplayer games that model pairwise interactions between players. The…

Computer Science and Game Theory · Computer Science 2016-03-17 Argyrios Deligkas , John Fearnley , Tobenna Peter Igwe , Rahul Savani

We develop a general game-theoretic framework for reasoning about strategic agents performing possibly costly computation. In this framework, many traditional game-theoretic results (such as the existence of a Nash equilibrium) no longer…

Computer Science and Game Theory · Computer Science 2008-09-02 Joseph Y. Halpern , Rafael Pass

Dynamic nonzero sum games are widely used to model multi agent decision making in control, economics, and related fields. Classical methods for computing Nash equilibria, especially in linear quadratic settings, rely on strong structural…

Neural and Evolutionary Computing · Computer Science 2026-01-07 Alireza Rezaee

We derive sublinear-time quantum algorithms for computing the Nash equilibrium of two-player zero-sum games, based on efficient Gibbs sampling methods. We are able to achieve speed-ups for both dense and sparse payoff matrices at the cost…

Quantum Physics · Physics 2019-04-08 Joran van Apeldoorn , András Gilyén

Distributed Nash equilibrium seeking of aggregative games is investigated and a continuous-time algorithm is proposed. The algorithm is designed by virtue of projected gradient play dynamics and distributed average tracking dynamics, and is…

Optimization and Control · Mathematics 2021-12-07 Shu Liang , Peng Yi , Yiguang Hong , Kaixiang Peng

The recently defined class of integer programming games (IPG) models situations where multiple self-interested decision makers interact, with their strategy sets represented by a finite set of linear constraints together with integer…

Computer Science and Game Theory · Computer Science 2023-04-25 Margarida Carvalho , Andrea Lodi , João Pedro Pedroso

Quantum games with incomplete information can be studied within a Bayesian framework. We analyze games quantized within the EWL framework [Eisert, Wilkens, and Lewenstein, Phys Rev. Lett. 83, 3077 (1999)]. We solve for the Nash equilibria…

Quantum Physics · Physics 2017-03-10 Neal Solmeyer , Radhakrishnan Balu

Computational aspects of solution notions such as Nash equilibrium have been extensively studied, including settings where the ultimate goal is to find an equilibrium that possesses some additional properties. Furthermore, in order to…

Computational Complexity · Computer Science 2023-05-09 Bruce M. Kapron , Koosha Samieefar

We study a distributionally robust optimization formulation (i.e., a min-max game) for two representative problems in Bayesian nonparametric estimation: Gaussian process regression and, more generally, linear inverse problems. Our…

Optimization and Control · Mathematics 2025-01-14 Xuhui Zhang , Jose Blanchet , Youssef Marzouk , Viet Anh Nguyen , Sven Wang

A recent body of experimental literature has studied empirical game-theoretical analysis, in which we have partial knowledge of a game, consisting of observations of a subset of the pure-strategy profiles and their associated payoffs to…

Computer Science and Game Theory · Computer Science 2014-02-13 John Fearnley , Martin Gairing , Paul Goldberg , Rahul Savani

The standard risk minimization paradigm of machine learning is brittle when operating in environments whose test distributions are different from the training distribution due to spurious correlations. Training on data from many…

Machine Learning · Computer Science 2020-03-20 Kartik Ahuja , Karthikeyan Shanmugam , Kush R. Varshney , Amit Dhurandhar

Algorithms for computing game-theoretic solutions have recently been applied to a number of security domains. However, many of the techniques developed for compact representations of security games do not extend to {\em Bayesian} security…

Computer Science and Game Theory · Computer Science 2016-04-19 Yuqian Li , Vincent Conitzer , Dmytro Korzhyk

This paper addresses the problem of fair equilibrium selection in graphical games. Our approach is based on the data structure called the {\em best response policy}, which was proposed by Kearns et al. \cite{kls} as a way to represent all…

Computer Science and Game Theory · Computer Science 2007-05-23 Edith Elkind , Leslie Ann Goldberg , Paul W. Goldberg

We introduce a new algorithm for the numerical computation of Nash equilibria of competitive two-player games. Our method is a natural generalization of gradient descent to the two-player setting where the update is given by the Nash…

Optimization and Control · Mathematics 2020-07-02 Florian Schäfer , Anima Anandkumar

The standard game-theoretic solution concept, Nash equilibrium, assumes that all players behave rationally. If we follow a Nash equilibrium and opponents are irrational (or follow strategies from a different Nash equilibrium), then we may…

Computer Science and Game Theory · Computer Science 2023-08-22 Sam Ganzfried

We develop a general game-theoretic framework for reasoning about strategic agents performing possibly costly computation. In this framework, many traditional game-theoretic results (such as the existence of a Nash equilibrium) no longer…

Computer Science and Game Theory · Computer Science 2014-12-10 Joseph Y. Halpern , Rafael Pass

This paper is concerned with complexity theoretic aspects of a general formulation of quantum game theory that models strategic interactions among rational agents that process and exchange quantum information. In particular, we prove that…

Computational Complexity · Computer Science 2022-12-28 John Bostanci , John Watrous