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The Dynamic Programming Method of Stochastic Differential Game for Functional Forward-Backward Stochastic System

机译:功能前向-后向随机系统随机微分博弈的动态规划方法

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This paper is devoted to a stochastic differential game (SDG) of decoupled functional forward-backward stochastic differential equation (FBSDE). For our SDG, the associated upper and lower value functions of the SDG are defined through the solution of controlled functional backward stochastic differential equations (BSDEs). Applying the Girsanov transformation method introduced by Buckdahn and Li (2008), the upper and the lower value functions are shown to be deterministic. We also generalize the Hamilton-Jacobi-Bellman-Isaacs (HJBI) equations to the path-dependent ones. By establishing the dynamic programming principal (DPP), we derive that the upper and the lower value functions are the viscosity solutions of the corresponding upper and the lower path-dependent HJBI equations, respectively.
机译:本文致力于解耦的功能前向-后向随机微分方程(FBSDE)的随机微分博弈(SDG)。对于我们的SDG,通过控制功能后向随机微分方程(BSDE)的解定义了SDG的相关上,下值函数。应用Buckdahn和Li(2008)引入的Girsanov变换方法,显示了上,下值函数是确定性的。我们还将汉密尔顿-雅各比-贝尔曼-艾萨克斯(HJBI)方程推广为与路径相关的方程。通过建立动态规划原理(DPP),我们得出上值和下值函数分别是相应的上,下路径相关HJBI方程的粘度解。

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