论文标题
不确定最小二乘正方形的策略梯度算法的全球融合固定最佳控制
Global Convergence of Policy Gradient Algorithms for Indefinite Least Squares Stationary Optimal Control
论文作者
论文摘要
我们考虑不确定最小二乘固定最佳控制的策略梯度算法，例如，具有不确定状态和输入惩罚矩阵的线性 - 季度调节器（LQR）。这样的设置在控制设计中具有重要的应用程序，具有冲突的目标，例如线性二次动态游戏。我们显示了这类无限期最小二乘问题的梯度，自然梯度和准牛顿政策的全球融合。
We consider policy gradient algorithms for the indefinite least squares stationary optimal control, e.g., linear-quadratic-regulator (LQR) with indefinite state and input penalization matrices. Such a setup has important applications in control design with conflicting objectives, such as linear quadratic dynamic games. We show the global convergence of gradient, natural gradient and quasi-Newton policies for this class of indefinite least squares problems.
