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This paper presents a pioneering investigation into discrete-time two-person non-zero-sum linear quadratic (LQ) stochastic games with random coefficients. We derive necessary and sufficient conditions for the existence of open-loop Nash…

Optimization and Control · Mathematics 2025-06-24 Yiwei Wu , Xun Li , Qingxin Meng

We study the problem of repeated play in a zero-sum game in which the payoff matrix may change, in a possibly adversarial fashion, on each round; we call these Online Matrix Games. Finding the Nash Equilibrium (NE) of a two player zero-sum…

Machine Learning · Computer Science 2020-04-06 Adrian Rivera Cardoso , Jacob Abernethy , He Wang , Huan Xu

Dynamic games provide a fundamental framework for multi-agent decision-making over time, yet computing feedback Nash equilibria (FNEs) in infinite-horizon discrete-time linear-quadratic (LQ) settings remains computationally challenging.…

Systems and Control · Electrical Eng. & Systems 2026-03-11 Shengyuan Huang , Xiaoguang Yang , Yifen Mu , Wenjun Mei

In this paper, we consider a linear quadratic stochastic two-person nonzero-sum differential game. Open-loop and closed-loop Nash equilibria are introduced. The existence of the former is characterized by the solvability of a system of…

Optimization and Control · Mathematics 2016-07-18 Jingrui Sun , Jiongmin Yong

Distributed Nash equilibrium (NE) seeking problem for multi-coalition games has attracted increasing attention in recent years, but the research mainly focuses on the case without agreement demand within coalitions. This paper considers a…

Optimization and Control · Mathematics 2021-12-10 Jialing Zhou , Yuezu Lv , Guanghui Wen , Jinhu Lv , Dezhi Zheng

We present a new, distributed method to compute approximate Nash equilibria in bimatrix games. In contrast to previous approaches that analyze the two payoff matrices at the same time (for example, by solving a single LP that combines the…

Computer Science and Game Theory · Computer Science 2018-10-12 Artur Czumaj , Argyrios Deligkas , Michail Fasoulakis , John Fearnley , Marcin Jurdziński , Rahul Savani

Nash equilibria provide a principled framework for modeling interactions in multi-agent decision-making and control. However, many equilibrium-seeking methods implicitly assume that each agent has access to the other agents' objectives and…

Computer Science and Game Theory · Computer Science 2026-03-19 Mahdis Rabbani , Navid Mojahed , Shima Nazari

Much work has been done on the computation of market equilibria. However due to strategic play by buyers, it is not clear whether these are actually observed in the market. Motivated by the observation that a buyer may derive a better…

Computer Science and Game Theory · Computer Science 2015-05-18 Bharat Adsul , Ch. Sobhan Babu , Jugal Garg , Ruta Mehta , Milind Sohoni

We consider quadratic, nonmonotone generalized Nash equilibrium problems with symmetric interactions among the agents. Albeit this class of games is known to admit a potential function, its formal expression can be unavailable in several…

Optimization and Control · Mathematics 2022-03-31 Filippo Fabiani , Andrea Simonetto , Paul J. Goulart

This paper investigates Nash equilibrium (NE) seeking problems for noncooperative games over multi-players networks with finite bandwidth communication. A distributed quantized algorithm is presented, which consists of local gradient play,…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-16 Ziqin Chen , Ji Ma , Shu Liang , Li Li

Nash equilibrium} (NE) can be stated as a formal theorem on a multilinear form, free of game theory terminology. On the other hand, inspired by this formalism, we state and prove a {\it multilinear minimax theorem}, a generalization of von…

Computer Science and Game Theory · Computer Science 2024-01-01 Bahman Kalantari

In this paper, we address the inverse problem for linear-quadratic differential non-cooperative games with output-feedback. Given players' stabilizing feedback laws, the goal is to find cost function parameters that lead to a game for which…

Optimization and Control · Mathematics 2024-10-27 Emin Martirosyan , Ming Cao

Designing efficient algorithms to find Nash equilibrium (NE) refinements in sequential games is of paramount importance in practice. Indeed, it is well known that the NE has several weaknesses, since it may prescribe to play sub-optimal…

Computer Science and Game Theory · Computer Science 2022-08-18 Martino Bernasconi , Alberto Marchesi , Francesco Trovò

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

We consider a subclass of $n$-player stochastic games, in which players have their own internal state/action spaces while they are coupled through their payoff functions. It is assumed that players' internal chains are driven by independent…

Machine Learning · Computer Science 2023-03-23 S. Rasoul Etesami

This paper investigates closed-loop Nash equilibria for discrete-time linear-quadratic (LQ) stochastic nonzero-sum difference games with random coefficients. Unlike existing works, we consider randomness in both state dynamics and cost…

Optimization and Control · Mathematics 2025-07-23 Qingxin Meng , Yiwei Wu

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 explore the power of semidefinite programming (SDP) for finding additive $epsilon$-approximate Nash equilibria in bimatrix games. We introduce an SDP relaxation for a quadratic programming formulation of the Nash equilibrium (NE) problem…

Optimization and Control · Mathematics 2019-08-16 Amir Ali Ahmadi , Jeffrey Zhang

Cross-silo federated learning (FL) is a distributed learning approach where clients of the same interest train a global model cooperatively while keeping their local data private. The success of a cross-silo FL process requires active…

Machine Learning · Computer Science 2022-02-01 Ning Zhang , Qian Ma , Xu Chen

We investigate the set of Nash equilibrium payoffs for two person differential games. The main result of the paper is the characterization of the set of Nash equilibrium payoffs in the terms of nonsmooth analysis. Also we obtain the…

Optimization and Control · Mathematics 2015-03-17 Yurii Averboukh