Policy Gradient Algorithms with Monte Carlo Tree Learning for Non-Markov Decision Processes

Tetsuro Morimura, Kazuhiro Ota, Kenshi Abe +1

Policy gradient (PG) is a reinforcement learning (RL) approach that optimizes a parameterized policy model for an expected return using gradient ascent. While PG can work well even…