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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…

最优化与控制 · 数学 2016-07-18 Jingrui Sun , Jiongmin Yong

Non-cooperative dynamic game theory provides a principled approach to modeling sequential decision-making among multiple noncommunicative agents. A key focus has been on finding Nash equilibria in two-agent zero-sum dynamic games under…

计算机科学与博弈论 · 计算机科学 2025-03-20 Kushagra Gupta , Ross Allen , David Fridovich-Keil , Ufuk Topcu

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…

最优化与控制 · 数学 2025-06-24 Yiwei Wu , Xun Li , Qingxin Meng

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…

最优化与控制 · 数学 2025-07-23 Qingxin Meng , Yiwei Wu

This paper investigates a two-person non-homogeneous linear-quadratic stochastic differential game (LQ-SDG, for short) in an infinite horizon for a system regulated by a time-invariant Markov chain. Both non-zero-sum and zero-sum LQ-SDG…

最优化与控制 · 数学 2024-08-26 Fan Wu , Xun Li , Jie Xiong , Xin Zhang

This paper is concerned with two-person mean-field linear-quadratic non-zero sum stochastic differential games in an infinite horizon. Both open-loop and closed-loop Nash equilibria are introduced. Existence of an open-loop Nash equilibrium…

最优化与控制 · 数学 2021-04-09 Xun Li , Jingtao Shi , Jiongmin Yong

In this paper, an open-loop two-person non-zero sum stochastic differential game is considered for forward-backward stochastic systems. More precisely, the controlled systems are described by a fully coupled nonlinear multi- dimensional…

最优化与控制 · 数学 2010-10-13 Maoning Tang , Qingxin Meng , Yongzheng Sun

Static potential games are non-cooperative games which admit a fictitious function, also referred to as a potential function, such that the minimizers of this function constitute a subset (or a refinement) of the Nash equilibrium strategies…

最优化与控制 · 数学 2021-03-08 Aathira Prasad , Puduru Viswanadha Reddy

In this paper, a Nash-type fictitious game framework is introduced to handle a time-inconsistent linear-quadratic optimal control. The Nash-type game in this framework is called fictitious as it is between the decision maker (called real…

最优化与控制 · 数学 2021-10-04 Yuan-Hua Ni , Binbin Si , Xinzhen Zhang

We identify structural assumptions which provide solvability of the Nash system arising from a linear-quadratic closed-loop game, with stable properties with respect to the number of players. In a setting of interactions governed by a…

最优化与控制 · 数学 2024-01-15 Marco Cirant , Davide Francesco Redaelli

Zero-sum games arise in a wide variety of problems, including robust optimization and adversarial learning. However, algorithms deployed for finding a local Nash equilibrium in these games often converge to non-Nash stationary points. This…

计算机科学与博弈论 · 计算机科学 2025-09-30 Kushagra Gupta , Xinjie Liu , Ross Allen , Ufuk Topcu , David Fridovich-Keil

We consider a two-player linear-state differential game, where one player intervenes continuously in the game, while the other implements an impulse control. When the impulse instants are exogenous, we obtain the classical result in…

最优化与控制 · 数学 2022-04-05 Utsav Sadana , Puduru Viswanadha Reddy , Georges Zaccour

We propose MultiLRSGA, an $h$-player extension of LRSGA for the computation of stable Nash equilibria in differentiable games. The method originates from the decomposition of the game Jacobian into symmetric and antisymmetric components,…

最优化与控制 · 数学 2026-05-06 Katherine Rossella Foglia , Vittorio Colao , Alfio Borzì

This paper investigates an inhomogeneous non-zero-sum linear-quadratic (LQ, for short) differential game problem whose state process and cost functional are regulated by a Markov chain. Under the $L^2$ stabilizability framework, we first…

最优化与控制 · 数学 2024-05-17 Fan Wu , Xun Li , Xin Zhang

In this paper we establish a new connection between a class of 2-player nonzero-sum games of optimal stopping and certain $2$-player nonzero-sum games of singular control. We show that whenever a Nash equilibrium in the game of stopping is…

最优化与控制 · 数学 2017-12-29 Tiziano De Angelis , Giorgio Ferrari

We analyze best response dynamics for finding a Nash equilibrium of an infinite horizon zero-sum stochastic linear quadratic dynamic game (LQDG) with partial and asymmetric information. We derive explicit expressions for each player's best…

系统与控制 · 电气工程与系统科学 2025-09-03 Yuxiang Guan , Iman Shames , Tyler H. Summers

This paper considers a two-player game where each player chooses a resource from a finite collection of options. Each resource brings a random reward. Both players have statistical information regarding the rewards of each resource.…

计算机科学与博弈论 · 计算机科学 2023-09-19 Mevan Wijewardena , Michael J. Neely

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…

计算机科学与博弈论 · 计算机科学 2026-03-19 Mahdis Rabbani , Navid Mojahed , Shima Nazari

This paper delves into studying the differences and connections between open-loop and closed-loop strategies for the linear quadratic (LQ) mean field games (MFGs) by the direct approach. The investigation begins with the finite-population…

最优化与控制 · 数学 2025-04-21 Yong Liang , Bing-Chang Wang , Huanshui Zhang

The paper is concerned with a zero-sum Stackelberg stochastic linear-quadratic (LQ, for short) differential game over finite horizons. Under a fairly weak condition, the Stackelberg equilibrium is explicitly obtained by first solving a…

最优化与控制 · 数学 2021-10-05 Jingrui Sun , Hanxiao Wang , Jiaqiang Wen
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