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Related papers: On Zero-Sum Stochastic Differential Games

200 papers

Synthesizing near-optimal mixed strategies for zero-sum differential games (ZSDGs) has been a longstanding challenge. Existing research mainly focuses on characterizing the theoretical value function, while the practical design of…

Optimization and Control · Mathematics 2026-05-13 Tao Xu , Wang Xi , Jianping He

A basic question for zero-sum repeated games consists in determining whether the mean payoff per time unit is independent of the initial state. In the special case of "zero-player" games, i.e., of Markov chains equipped with additive…

Optimization and Control · Mathematics 2015-10-20 Marianne Akian , Stéphane Gaubert , Antoine Hochart

This paper is concerned with the switching game of a one-dimensional backward stochastic differential equation (BSDE). The associated Bellman-Isaacs equation is a system of matrix-valued BSDEs living in a special unbounded convex domain…

Probability · Mathematics 2013-11-26 Ying Hu , Shanjian Tang

This paper addresses a continuous-time risk-minimizing two-player zero-sum stochastic differential game (SDG), in which each player aims to minimize its probability of failure. Failure occurs in the event when the state of the game enters…

Optimization and Control · Mathematics 2023-08-23 Apurva Patil , Yujing Zhou , David Fridovich-Keil , Takashi Tanaka

The paper is concerned with a zero-sum differential game in the case where a payoff is determined by the exit time, that is, the first time when the system leaves the game domain. Additionally, we assume that a part of domain's boundary is…

Optimization and Control · Mathematics 2024-05-02 Ekaterina Kolpakova

We develop here the Stochastic Perron Method in the framework of two-player zero-sum differential games. We consider the formulation of the game where both players play, symmetrically, feed-back strategies (as in [CR09] or [PZ12]) as…

Optimization and Control · Mathematics 2014-02-20 Mihai Sîrbu

In this paper we study the zero-sum and nonzero-sum differential games with not assuming Isaacs condition. Along with the partition $\pi$ of the time interval $[0,T]$, we choose the suitable random non-anticipative strategy with delay to…

Optimization and Control · Mathematics 2015-07-20 Juan Li , Wenqiang Li

Semidefinite programs (SDPs) play a crucial role in control theory, traditionally as a computational tool. Beyond computation, the duality theory in convex optimization also provides valuable analytical insights and new proofs of classical…

Optimization and Control · Mathematics 2025-04-04 Yuto Watanabe , Chih-Fan Pai , Yang Zheng

We study zero-sum games, a variant of the classical combinatorial Subtraction games (studied for example in the monumental work "Winning Ways", by Berlekamp, Conway and Guy), called Cumulative Subtraction (CS). Two players alternate in…

Combinatorics · Mathematics 2020-02-14 Gal Cohensius , Urban Larsson , Reshef Meir , David Wahlstedt

Stochastic games are a classical model in game theory in which two opponents interact and the environment changes in response to the players' behavior. The central solution concepts for these games are the discounted values and the value,…

Optimization and Control · Mathematics 2019-12-12 Miquel Oliu-Barton

This paper develops an algorithm for upper- and lower-bounding the value function for a class of linear time-varying games subject to convex control sets. In particular, a two-player zero-sum differential game is considered where the…

Optimization and Control · Mathematics 2025-03-12 Vincent Liu , Chris Manzie , Peter M. Dower

We study two classes of zero-sum stochastic games with compact action sets and a finite product state space. These two classes assume a communication property on the state spaces of the players. For strongly communicating on one side games,…

Optimization and Control · Mathematics 2019-07-03 Tristan Garrec

We consider reflected backward stochastic differential equations with two optional barriers of class (D) satisfying Mokobodzki's separation condition and coefficient which is only continuous and non-increasing. We assume that data are…

Probability · Mathematics 2021-12-02 Tomasz Klimsiak , Maurycy Rzymowski

Zero-determinant strategies are memory-one strategies in repeated games which unilaterally enforce linear relations between expected payoffs of players. Recently, the concept of zero-determinant strategies was extended to the class of…

Optimization and Control · Mathematics 2022-09-07 Masahiko Ueda

Candogan et al. (2011) provide an orthogonal direct-sum decomposition of finite games into potential, harmonic and nonstrategic components. In this paper we study the issue of decomposing games that are strategically equivalent from a…

Computer Science and Game Theory · Computer Science 2020-04-01 Joseph Abdou , Nikolaos Pnevmatikos , Marco Scarsini , Xavier Venel

We consider multiplayer stochastic games in which the payoff of each player is a bounded and Borel-measurable function of the infinite play. By using a generalization of the technique of Martin (1998) and Maitra and Sudderth (1998), we show…

Optimization and Control · Mathematics 2022-08-26 János Flesch , Eilon Solan

In this paper, we examine a class of $\alpha$-potential stochastic differential games with random coefficients via the backward stochastic differential equations (BSDEs) approach. Specifically, we show that the first and second order linear…

Optimization and Control · Mathematics 2025-07-18 Xin Guo , Xun Li , Liangquan Zhang

We study optimal behavior of energy producers under a CO_2 emission abatement program. We focus on a two-player discrete-time model where each producer is sequentially optimizing her emission and production schedules. The game-theoretic…

Optimization and Control · Mathematics 2010-08-24 Michael Ludkovski

Decentralized team problems where players have asymmetric information about the state of the underlying stochastic system have been actively studied, but \emph{games} between such teams are less understood. We consider a general model of…

Multiagent Systems · Computer Science 2021-09-29 Dhruva Kartik , Ashutosh Nayyar , Urbashi Mitra

Zero-sum stochastic games are easy to solve as they can be cast as simple Markov decision processes. This is however not the case with general-sum stochastic games. A fairly general optimization problem formulation is available for…

Machine Learning · Computer Science 2015-07-02 H. L. Prasad , Shalabh Bhatnagar