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We define a class of zero-sum games with combinatorial structure, where the best response problem of one player is to maximize a submodular function. For example, this class includes security games played on networks, as well as the problem…

Computer Science and Game Theory · Computer Science 2017-12-04 Bryan Wilder

For a zero-sum stochastic game which does not satisfy the Isaacs condition, we provide a value function representation for an Isaacs-type equation whose Hamiltonian lies in between the lower and upper Hamiltonians, as a convex combination…

Probability · Mathematics 2016-09-30 Daniel Hernández-Hernández , Mihai Sîrbu

A two-person zero-sum infinite dimensional differential game of infinite duration with discounted payoff involving hybrid controls is studied. The minimizing player is allowed to take continuous, switching and impulse controls whereas the…

Optimization and Control · Mathematics 2009-09-29 A J Shaiju , Sheetal Dharmatti

We consider a finite-horizon, zero-sum game in which both players control a stochastic differential equation by invoking impulses. We derive a control randomization formulation of the game and use the existence of a value for the randomized…

Optimization and Control · Mathematics 2025-05-13 Magnus Perninge

We investigate a two-player zero-sum stochastic differential game problem with the state process being constrained in a connected bounded closed domain, and the cost functional described by the solution of a generalized backward stochastic…

Probability · Mathematics 2017-05-12 Lishun Xiao , Dejian Tian

In this paper we investigate two-player zero-sum stochastic differential games with an ergodic payoff, in which the diffusion coefficient does not need to be non-degenerate. We first establish the existence of a viscosity solution to the…

Optimization and Control · Mathematics 2026-01-21 Juan Li , Wenqiang Li , Yanwei Li , Huaizhong Zhao

Maximum entropy reinforcement learning (RL) methods have been successfully applied to a range of challenging sequential decision-making and control tasks. However, most of existing techniques are designed for discrete-time systems. As a…

Optimization and Control · Mathematics 2020-09-29 Jeongho Kim , Insoon Yang

In this note, we discuss a class of time-dependent Hamilton-Jacobi equations depending on a function of time, this function being chosen in order to keep the maximum of the solution to the constant value 0. The main result of the note is…

Analysis of PDEs · Mathematics 2015-02-16 Sepideh Mirrahimi , Jean-Michel Roquejoffre

We consider a class of two-player zero-sum stochastic games with finite state and compact control spaces, which we call stochastic shortest path (SSP) games. They are undiscounted total cost stochastic dynamic games that have a cost-free…

Optimization and Control · Mathematics 2014-12-31 Huizhen Yu

The purpose of this paper is to describe the numerical solution of the Hamilton-Jacobi-Bellman (HJB) for an optimal control problem for quantum spin systems. This HJB equation is a first order nonlinear partial differential equation defined…

Quantum Physics · Physics 2011-10-05 Srinivas Sridharan , Matthew R. James

We consider a convexity constrained Hamilton-Jacobi-Bellman-type obstacle problem for the value function of a zero-sum differential game with asymmetric information. We propose a convexity-preserving probabilistic numerical scheme for the…

Numerical Analysis · Mathematics 2021-03-26 Ľubomír Baňas , Giorgio Ferrari , Tsiry A. Randrianasolo

In this paper we deal with the problem of existence of a smooth solution of the Hamilton-Jacobi-Bellman-Isaacs (HJBI for short) system of equations associated with nonzero-sum stochastic differential games. We consider the problem in…

Analysis of PDEs · Mathematics 2018-10-24 Said Hamadene , Paola Mannucci

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

We consider two-player zero-sum differential games (ZSDGs), where the state process (dynamical system) depends on the random initial condition and the state process's distribution, and the objective functional includes the state process's…

Optimization and Control · Mathematics 2020-05-26 Jun Moon , Tamer Basar

In this paper we study zero-sum two-player stochastic differential games with the help of theory of Backward Stochastic Differential Equations (BSDEs). At the one hand we generalize the results of the pioneer work of Fleming and Souganidis…

Probability · Mathematics 2011-02-19 Rainer Buckdahn , Juan Li

In this article we study a finite horizon optimal control problem with monotone controls. We consider the associated Hamilton-Jacobi-Bellman (HJB) equation which characterizes the value function. We consider the totally discretized problem…

Optimization and Control · Mathematics 2014-07-08 Eduardo A. Philipp , Laura S. Aragone , Lisandro A. Parente

We introduce two-level discounted games played by two players on a perfect-information stochastic game graph. The upper level game is a discounted game and the lower level game is an undiscounted reachability game. Two-level games model…

Logic in Computer Science · Computer Science 2010-06-09 Krishnendu Chatterjee , Rupak Majumdar

Zero-sum stochastic games generalize the notion of Markov Decision Processes (i.e. controlled Markov chains, or stochastic dynamic programming) to the 2-player competitive case : two players jointly control the evolution of a state…

Optimization and Control · Mathematics 2019-05-17 Jérôme Renault

We consider a zero-sum stochastic game for continuous-time Markov chain with countable state space and unbounded transition and pay-off rates. The additional feature of the game is that the controllers together with taking actions are also…

Optimization and Control · Mathematics 2020-09-01 Chandan Pal , Subhamay Saha

Many optimal control problems are formulated as two point boundary value problems (TPBVPs) with conditions of optimality derived from the Hamilton-Jacobi-Bellman (HJB) equations. In most cases, it is challenging to solve HJBs due to the…

Optimization and Control · Mathematics 2019-07-25 Sixiong You , Ran Dai , Ping Lu
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