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In this paper, we study the problem of learning the set of pure strategy Nash equilibria and the exact structure of a continuous-action graphical game with quadratic payoffs by observing a small set of perturbed equilibria. A…

Computer Science and Game Theory · Computer Science 2019-11-12 Adarsh Barik , Jean Honorio

We consider the problem of learning sparse polymatrix games from observations of strategic interactions. We show that a polynomial time method based on $\ell_{1,2}$-group regularized logistic regression recovers a game, whose Nash…

Machine Learning · Computer Science 2019-01-30 Asish Ghoshal , Jean Honorio

Empirical game-theoretic analysis (EGTA) is primarily focused on learning the equilibria of simulation-based games. Recent approaches have tackled this problem by learning a uniform approximation of the game's utilities, and then applying…

Computer Science and Game Theory · Computer Science 2022-08-15 Cyrus Cousins , Bhaskar Mishra , Enrique Areyan Viqueira , Amy Greenwald

In many smart infrastructure applications flexibility in achieving sustainability goals can be gained by engaging end-users. However, these users often have heterogeneous preferences that are unknown to the decision-maker tasked with…

Computer Science and Game Theory · Computer Science 2017-04-27 Ioannis C. Konstantakopoulos , Lillian J. Ratliff , Ming Jin , S. Shankar Sastry , Costas Spanos

We develop a flexible stochastic approximation framework for analyzing the long-run behavior of learning in games (both continuous and finite). The proposed analysis template incorporates a wide array of popular learning algorithms,…

Computer Science and Game Theory · Computer Science 2023-07-04 Panayotis Mertikopoulos , Ya-Ping Hsieh , Volkan Cevher

Learning problems commonly exhibit an interesting feedback mechanism wherein the population data reacts to competing decision makers' actions. This paper formulates a new game theoretic framework for this phenomenon, called "multi-player…

Computer Science and Game Theory · Computer Science 2022-04-08 Adhyyan Narang , Evan Faulkner , Dmitriy Drusvyatskiy , Maryam Fazel , Lillian J. Ratliff

Zero-sum games are a fundamental setting for adversarial training and decision-making in multi-agent learning (MAL). Existing methods often ensure convergence to (approximate) Nash equilibria by introducing a form of regularization. Yet,…

Multiagent Systems · Computer Science 2026-02-10 Tuo Zhang , Leonardo Stella

Concavity and its refinements underpin tractability in multiplayer games, where players independently choose actions to maximize their own payoffs which depend on other players' actions. In concave games, where players' strategy sets are…

Computer Science and Game Theory · Computer Science 2025-12-12 Vincent Leon , Iosif Sakos , Ryann Sim , Antonios Varvitsiotis

We analyze the sample complexity of learning graphical games from purely behavioral data. We assume that we can only observe the players' joint actions and not their payoffs. We analyze the sufficient and necessary number of samples for the…

Computer Science and Game Theory · Computer Science 2018-11-16 Jean Honorio

We study a model of selfish resource allocation that seeks to incorporate dependencies among resources as they exist in modern networked environments. Our model is inspired by utility functions with constant elasticity of substitution (CES)…

Computer Science and Game Theory · Computer Science 2017-05-04 Matthias Feldotto , Lennart Leder , Alexander Skopalik

In this paper, we examine the long-run behavior of regularized, no-regret learning in finite games. A well-known result in the field states that the empirical frequencies of no-regret play converge to the game's set of coarse correlated…

Computer Science and Game Theory · Computer Science 2023-11-07 Victor Boone , Panayotis Mertikopoulos

We tackle the problem of learning equilibria in simulation-based games. In such games, the players' utility functions cannot be described analytically, as they are given through a black-box simulator that can be queried to obtain noisy…

Computer Science and Game Theory · Computer Science 2020-02-26 Alberto Marchesi , Francesco Trovò , Nicola Gatti

Recent extensions to dynamic games of the well-known fictitious play learning procedure in static games were proved to globally converge to stationary Nash equilibria in two important classes of dynamic games (zero-sum and…

Computer Science and Game Theory · Computer Science 2022-07-08 Lucas Baudin , Rida Laraki

We tackle a fundamental problem in empirical game-theoretic analysis (EGTA), that of learning equilibria of simulation-based games. Such games cannot be described in analytical form; instead, a black-box simulator can be queried to obtain…

Computer Science and Game Theory · Computer Science 2019-06-03 Enrique Areyan Viqueira , Cyrus Cousins , Eli Upfal , Amy Greenwald

In this work, we study the problem of learning a nonlinear dynamical system by parameterizing its dynamics using basis functions. We assume that disturbances occur at each time step with an arbitrary probability $p$, which models the…

Optimization and Control · Mathematics 2025-03-24 Haixiang Zhang , Baturalp Yalcin , Javad Lavaei , Eduardo D. Sontag

We study the sample complexity of identifying the pure strategy Nash equilibrium (PSNE) in a two-player zero-sum matrix game with noise. Formally, we are given a stochastic model where any learner can sample an entry $(i,j)$ of the input…

Machine Learning · Computer Science 2023-11-29 Arnab Maiti , Ross Boczar , Kevin Jamieson , Lillian J. Ratliff

There has been substantial progress on finding game-theoretic equilibria. Most of that work has focused on games with finite, discrete action spaces. However, many games involving space, time, money, and other fine-grained quantities have…

Computer Science and Game Theory · Computer Science 2025-10-28 Carlos Martin , Tuomas Sandholm

In this paper we study the problem of exact recovery of the pure-strategy Nash equilibria (PSNE) set of a graphical game from noisy observations of joint actions of the players alone. We consider sparse linear influence games --- a…

Computer Science and Game Theory · Computer Science 2019-05-28 Asish Ghoshal , Jean Honorio

In this paper we consider continuity of the set of Nash equilibria and approximate Nash equilibria for parameterized games. For parameterized games with unique Nash equilibria, the continuity of this equilibrium mapping is well-known.…

Optimization and Control · Mathematics 2020-07-10 Zachary Feinstein

We study the complexity of computing equilibria in binary public goods games on undirected graphs. In such a game, players correspond to vertices in a graph and face a binary choice of performing an action, or not. Each player's decision…

Computer Science and Game Theory · Computer Science 2023-05-22 Max Klimm , Maximilian J. Stahlberg
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