Reinforcement Learning, Markov Decision Process, Markov Chains, Deep Learning, Artificial Intelligence.
where outcomes are partly random and partly under the control of a decision maker. At each time step, the process is in some state s and the decision maker may choose any action a that is available in state s. The process responds at the next time step by randomly moving into a new state s ′ and