Reinforcement Learning, Gaming, Deep Learning.
actor then updates its policy based on the feedback from the critic. Policy gradient methods: Policy gradient methods directly optimize the policy function. They use the gradient of the expected reward with respect to the policy function to update the policy. Q-learning: Q-learning is a value-based