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Worst-case hardness results for most equilibrium computation problems have raised the need for beyond-worst-case analysis. To this end, we study the smoothed complexity of finding pure Nash equilibria in Network Coordination Games, a…

Computational Complexity · Computer Science 2019-02-27 Shant Boodaghians , Rucha Kulkarni , Ruta Mehta

We design a distributed algorithm for learning Nash equilibria over time-varying communication networks in a partial-decision information scenario, where each agent can access its own cost function and local feasible set, but can only…

Optimization and Control · Mathematics 2020-09-11 Mattia Bianchi , Sergio Grammatico

We address the Nash equilibrium problem in a partial-decision information scenario, where each agent can only observe the actions of some neighbors, while its cost possibly depends on the strategies of other agents. Our main contribution is…

Optimization and Control · Mathematics 2021-05-07 Mattia Bianchi , Giuseppe Belgioioso , Sergio Grammatico

In noncooperative Nash games, equilibria are often inefficient. This is exemplified by the Prisoner's Dilemma and was first provably shown in the 1980s. Since then, understanding the quality of Nash equilibrium (NE) received considerable…

Optimization and Control · Mathematics 2024-12-02 Yuyang Qiu , Farzad Yousefian , Brian Zhang

We study the complexity of computing stationary Nash equilibrium (NE) in n-player infinite-horizon general-sum stochastic games. We focus on the problem of computing NE in such stochastic games when each player is restricted to choosing a…

Computer Science and Game Theory · Computer Science 2022-11-30 Yujia Jin , Vidya Muthukumar , Aaron Sidford

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

This paper presents a new distributed algorithm that leverages heavy-ball momentum and a consensus-based gradient method to find a Nash equilibrium (NE) in a class of non-cooperative convex games with unconstrained action sets. In this…

Computer Science and Game Theory · Computer Science 2023-06-06 Duong Thuy Anh Nguyen , Duong Tung Nguyen , Angelia Nedich

In this paper, we consider a distributed Bayesian Nash equilibrium (BNE) seeking problem in incomplete-information aggregative games, which is a generalization of Bayesian games and deterministic aggregative games. We handle the aggregation…

Optimization and Control · Mathematics 2023-09-19 Hanzheng Zhang , Guanpu Chen , Huashu Qin

This paper presents a new primal-dual method for computing an equilibrium of generalized (continuous) Nash game (referred to as generalized Nash equilibrium problem (GNEP)) where each player's feasible strategy set depends on the other…

Computer Science and Game Theory · Computer Science 2022-03-04 Jong Gwang Kim

Pseudo-games are a natural and well-known generalization of normal-form games, in which the actions taken by each player affect not only the other players' payoffs, as in games, but also the other players' strategy sets. The solution…

Computer Science and Game Theory · Computer Science 2022-10-20 Denizalp Goktas , Amy Greenwald

This paper considers the distributed strategy design for Nash equilibrium (NE) seeking in multi-cluster games under a partial-decision information scenario. In the considered game, there are multiple clusters and each cluster consists of a…

Optimization and Control · Mathematics 2022-06-08 Min Meng , Xiuxian Li

In this work, we study stochastic non-cooperative games, where only noisy black-box function evaluations are available to estimate the cost function for each player. Since each player's cost function depends on both its own decision…

Computer Science and Game Theory · Computer Science 2025-11-18 Haidong Li , Anzhi Sheng , Yijie Peng , Long Wang

Nash equilibrium is a central concept in game theory. Several Nash solvers exist, yet none scale to normal-form games with many actions and many players, especially those with payoff tensors too big to be stored in memory. In this work, we…

Computer Science and Game Theory · Computer Science 2022-02-07 Ian Gemp , Rahul Savani , Marc Lanctot , Yoram Bachrach , Thomas Anthony , Richard Everett , Andrea Tacchetti , Tom Eccles , János Kramár

This paper deals with the complexity of the problem of computing a pure Nash equilibrium for discrete preference games and network coordination games beyond $O(\log n)$-treewidth and tree metric spaces. First, we estimate the number of…

Computer Science and Game Theory · Computer Science 2022-07-05 Takashi Ishizuka , Naoyuki Kamiyama

We study the performance of the gradient play algorithm for stochastic games (SGs), where each agent tries to maximize its own total discounted reward by making decisions independently based on current state information which is shared…

Machine Learning · Computer Science 2023-12-08 Runyu Zhang , Zhaolin Ren , Na Li

In dynamic games with shared constraints, Generalized Nash Equilibria (GNE) are often computed using the normalized solution concept, which assumes identical Lagrange multipliers for shared constraints across all players. While widely used,…

Robotics · Computer Science 2025-11-07 Mark Pustilnik , Francesco Borrelli

We consider generalized Nash equilibrium problems (GNEPs) with linear coupling constraints affected by both local (i.e., agent-wise) and global (i.e., shared resources) disturbances taking values in polyhedral uncertainty sets. By making…

Systems and Control · Electrical Eng. & Systems 2023-04-07 Marta Fochesato , Filippo Fabiani , John Lygeros

In this paper, the generalized Nash equilibrium (GNE) seeking problem for continuous games with coupled affine inequality constraints is investigated in a partial-decision information scenario, where each player can only access its…

Computer Science and Game Theory · Computer Science 2022-07-29 Min Meng , Xiuxian Li

Stochastic games generalize Markov decision processes (MDPs) to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards determined by multiplayer matrix games at each state. We…

Computer Science and Game Theory · Computer Science 2013-01-18 Michael Kearns , Yishay Mansour , Satinder Singh

Dynamic games can be an effective approach to modeling interactive behavior between multiple non-cooperative agents and they provide a theoretical framework for simultaneous prediction and control in such scenarios. In this work, we propose…

Systems and Control · Electrical Eng. & Systems 2022-09-19 Edward L. Zhu , Francesco Borrelli
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