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Markov Decision Process

To avoid load problems and computational difficulties, the Agent-Environment interaction is considered as a MDP. MDP is a discrete time stochastic control process. At each time step, the process is in a 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(s,s').

Under these hypotheses, the Agent-Environment interaction can be schematized as follows:

• The agent and the environment interact at discrete intervals over time, t = 0, 1, 2, … n.
• At each interval, the agent receives a representation of the state st of the environment.
• Each element s_t of ...