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In this paper, we investigate the noncooperative games of multi-agent systems. Different from existing noncooperative games, our formulation involves the high-order nonlinear dynamics of players, and the communication topologies among…

Systems and Control · Electrical Eng. & Systems 2021-12-17 Zhenhua Deng , Jin Luo

This paper studies partially observable two-person zero-sum semi-Markov games under a probability criterion, in which the system state may not be completely observed. It focuses on the probability that the accumulated rewards of player 1…

Optimization and Control · Mathematics 2025-08-26 Xin Wen , Li Xia , Zhihui Yu

This paper is concerned with a new type of differential game problems of forwardbackward stochastic systems. There are three distinguishing features: Firstly, our game systems are forward-backward doubly stochastic differential equations,…

Optimization and Control · Mathematics 2015-10-09 Eddie C. M. Hui , Hua Xiao

We consider time-homogeneous uniformly nondegenerate stochastic differential games in domains and propose constructing $\varepsilon$-optimal strategies and policies by using adjoint Markov strategies and adjoint Markov policies which are…

Optimization and Control · Mathematics 2019-03-26 N. V. Krylov

This paper focuses on zero-sum stochastic differential games in the framework of forward-backward stochastic differential equations on a finite time horizon with both players adopting impulse controls. By means of BSDE methods, in…

Optimization and Control · Mathematics 2021-04-08 Liangquan Zhang

We study a two-player zero-sum stochastic differential game with both players adopting impulse controls, on a finite time horizon. The Hamilton-Jacobi-Bellman-Isaacs (HJBI) partial differential equation of the game turns out to be a…

Probability · Mathematics 2012-06-26 Andrea Cosso

This paper investigates online stochastic aggregative games subject to local set constraints and time-varying coupled inequality constraints, where each player possesses a time-varying expectation-valued cost function relying on not only…

Optimization and Control · Mathematics 2025-11-18 Kaixin Du , Min Meng

In this paper, we study a non-zero-sum game with two players, where each of the players plays what we call Bermudan strategies and optimizes a general non-linear assessment functional of the pay-off. By using a recursive construction, we…

Optimization and Control · Mathematics 2023-11-03 Miryana Grigorova , Marie-Claire Quenez , Yuan Peng

This paper investigates a class of linear-quadratic-Gaussian risk-sensitive graphon mean-field games, involving an asymptotically infinite population of heterogeneous agents distributed across an asymptotically infinite network, where each…

Optimization and Control · Mathematics 2026-04-28 Tian Chen , Minyi Huang

We study zero-sum stochastic differential games with player dynamics governed by a nondegenerate controlled diffusion process. Under the assumption of uniform stability, we establish the existence of a solution to the Isaac's equation for…

Optimization and Control · Mathematics 2019-03-20 Ari Arapostathis , Vivek S. Borkar , K. Suresh Kumar

This paper is concerned with non-zero sum differential games of mean-field stochastic differential equations with partial information and convex control domain. First, applying the classical convex variations, we obtain stochastic maximum…

Optimization and Control · Mathematics 2016-01-11 Hua Xiao , Shuaiqi Zhang

We develop a game-theoretic framework for adversarially robust optimal safe predefined-time stabilization of parameter-dependent nonlinear dynamical systems with nonquadratic cost functionals. Our approach ensures that all system…

Optimization and Control · Mathematics 2025-11-20 Nick-Marios T. Kokolakis , Shanqing Liu , Jerome Darbon , Rahul Mangharam , George Em Karniadakis

We discuss similarities and differences between systems of interacting players maximizing their individual payoffs and particles minimizing their interaction energy. Long-run behavior of stochastic dynamics of spatial games with multiple…

Statistical Mechanics · Physics 2009-11-10 Jacek Miekisz

We study decentralized learning in two-player zero-sum discounted Markov games where the goal is to design a policy optimization algorithm for either agent satisfying two properties. First, the player does not need to know the policy of the…

Computer Science and Game Theory · Computer Science 2023-03-07 Zhuoqing Song , Jason D. Lee , Zhuoran Yang

Let $T:X\to X $ and $S:Y \to Y$ be continuous maps defined on compact sets. Let $$\varphi_i(\mu,\nu)=\int_{X \times Y} A_i(x,y) d\mu(x) d\nu(y)\;\;{for} \;\; i=1,2,$$ where $\mu$ is $T$-invariant and $\nu$ is $S$-invariant, be pay-off…

Dynamical Systems · Mathematics 2019-02-25 Rafael R. Souza

This paper considers mean field games in a multi-agent Markov decision process (MDP) framework. Each player has a continuum state and binary action, and benefits from the improvement of the condition of the overall population. Based on an…

Optimization and Control · Mathematics 2021-01-05 Minyi Huang , Yan Ma

We analyse the computational complexity of finding Nash equilibria in simple stochastic multiplayer games. We show that restricting the search space to equilibria whose payoffs fall into a certain interval may lead to undecidability. In…

Computer Science and Game Theory · Computer Science 2010-06-24 Michael Ummels , Dominik Wojtczak

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

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…

Optimization and Control · Mathematics 2024-05-17 Fan Wu , Xun Li , Xin Zhang

Constrained Markov games offer a formal mathematical framework for modeling multi-agent reinforcement learning problems where the behavior of the agents is subject to constraints. In this work, we focus on the recently introduced class of…

Machine Learning · Computer Science 2024-02-29 Philip Jordan , Anas Barakat , Niao He