Policy Gradient Methods: REINFORCE, Actor-Critic, and the Policy Gradient Theorem (S&B Ch. 13)

Almost all the algorithms/methods covered so far have been action-value methods (except gradient-bandit algorithms, Section 2.8 ). Action-value methods learn the values of actions and then derive the policy thereafter to select actions based on their estimated action values. Here, we explicitly learn a parametrized policy that can select actions without consulting a value function. A value…