论文标题
线性二次观察到的stackelberg随机差异游戏,并带有应用
A Linear Quadratic Partially Observed Stackelberg Stochastic Differential Game with Applications
论文作者
论文摘要
本文涉及一个线性界面部分观察到的stackelberg随机差分游戏,具有相关状态和观察噪声,其中扩散系数不包含控制变量,并且控制集不一定是凸。领导者和追随者都有自己的观察方程式,而领导者可用的信息过滤也包含在追随者中。通过尖峰变化,状态分解和向后分离技术,得出了Stackelberg平衡点的必要条件。在追随者的问题中,最佳控制的状态估计反馈可以通过前向后的随机差异滤波方程和一些riccati方程来表示。在领导者的问题中,通过创新过程,最佳控制的状态估计反馈由随机微分滤波方程,半摩托车过程和三个高维Riccati方程表示。同时,可以通过一个新的组合想法来确保对伴随方程的独特性和解决方案的唯一性和存在,并且将一种完全耦合的前回向随机微分方程与过滤一起研究。然后,在特殊情况下,我们给出了Stackelberg平衡点的明确表达式。作为一种实际应用,研究了一个不对称信息的鼓舞人心的动态广告问题,并通过数值模拟说明了理论结果的有效性和合理性。此外,详细分析了最佳控制,状态估计与某些实际参数之间的关系。
This paper is concerned with a linear-quadratic partially observed Stackelberg stochastic differential game with correlated state and observation noises, where the diffusion coefficient does not contain the control variable and the control set is not necessarily convex. Both the leader and the follower have their own observation equations, and the information filtration available to the leader is contained in that to the follower. By spike variational, state decomposition and backward separation techniques, necessary and sufficient conditions of the Stackelberg equilibrium points are derived. In the follower's problem, the state estimation feedback of optimal control can be represented by a forward-backward stochastic differential filtering equation and some Riccati equation. In the leader's problem, via the innovation process, the state estimation feedback of optimal control is represented by a stochastic differential filtering equation, a semi-martingale process and three high-dimensional Riccati equations. At the same time, the uniqueness and existence of solutions to adjoint equations can be guaranteed by a new combined idea, and a kind of fully coupled forward-backward stochastic differential equations with filtering is studied as a by-product. Then we give explicit expressions of Stackelberg equilibrium points in a special case. As a practical application, an inspiring dynamic advertising problem with asymmetric information is studied, and the effectiveness and reasonability of the theoretical result is illustrated by numerical simulations. Moreover, the relationship between optimal control, state estimate and some practical parameters is analyzed in detail.