标题： 带有不对称信息不确定性的随机线性二次Stackelberg微分博弈：鲁棒优化方法 显示英文标题

标题： Stochastic Linear-Quadratic Stackelberg Differential Game with Asymmetric Informational Uncertainties: Robust Optimization Approach

摘要： 本文研究的是一个具有不对称信息不确定性的两人零和不定随机线性二次斯塔克尔伯格微分博弈，其中领导者和跟随者都面临不同的未知扰动。 我们采用鲁棒优化方法和软约束分析，首先由跟随者求解一个最小最大随机线性二次最优控制问题。 然后，领导者在扩展空间中处理一个前向后向随机微分方程的最大最小随机线性二次最优控制问题。 通过一些里卡蒂方程，利用解耦技术以更明确的形式给出了鲁棒斯塔克尔伯格均衡的状态反馈表示。 显示英文摘要

摘要： This paper is concerned with a two-person zero-sum indefinite stochastic linear-quadratic Stackelberg differential game with asymmetric informational uncertainties, where both the leader and follower face different and unknown disturbances. We take a robust optimization approach and soft-constraint analysis, a min-max stochastic linear-quadratic optimal control problem is solved by the follower firstly. Then, the leader deal with a max-min stochastic linear-quadratic optimal control problem of forward-backward stochastic differential equations in an augmented space. State feedback representation of the robust Stackelberg equilibrium is given in a more explicit form by decoupling technique, via some Riccati equations.