Markov Decision Process (MDP)
Revision as of 05:53, 27 May 2018 by BPeat (talk | contribs) (Created page with "[http://www.youtube.com/results?search_query=deep+reinforcement+q+learning+artificial+intelligence+ Youtube search...] * Deep Reinforcement Learning (DRL) https://upload...")
Used where outcomes are partly random and partly under the control of a decision maker. MDP is a discrete time stochastic control process. 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 giving the decision maker a corresponding reward R_{a}(s,s')} R_a(s,s'). The probability that the process moves into its new state s' is influenced by the chosen action.
