Siqiao Mu

On the Second-Order Convergence of Biased Policy Gradient Algorithms

2023 · arXiv (Cornell University)

Since the objective functions of reinforcement learning problems are typically highly nonconvex, it is desirable that policy gradient, the most popular algorithm, escapes saddle points and arrives at second-order stationary points. Existing results only consider …