Reinforcement Learning, Artificial Intelligence, Deep Learning.
update its policy based on the expected future rewards and the trace of its previous experiences. Second, they can be used to solve problems with continuous states and actions, as the agent can update its policy based on the gradient of the value function. Third, they have been proven to be more