Policy gradient methods are a class of algorithms in reinforcement learning that optimize the policy directly. In reinforcement learning, a policy is a mapping from states of the environment to actions to be taken when in those states. The objective of policy gradient methods is to find the optimal policy that maximizes the expected cumulative