Markov Decision Process (MDP) is influenced by decisions and stochasticity

A Markov Decison Process (MDP) is a markov process that is partly influenced by decision and partly by stochasticity.

A MDP has:

• $S$ : set of states; the state space
• $A$ : set of actions; the action space
• $P_a(s,s^{\prime })$ : probability a transition happens from $s$ to $s^{\prime }$ due to action $a$
• $R_a(s,s^{\prime })$: immediate reward/payoff/value due to state transition

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