Problem 2 (10 points): Consider the Markov Decision Process (MDP) with transition probabilities and reward function as given in the tables below. Assume the discount factor   = 1 (i.e , there is no actual discounting).T(8 ; 2 # 0.5 0.5R(8 1B B B J: BR( s.We follow the steps of the Policy Iteration algorithm as explained in the class Write down the Bellman equation: The initial policy is T(A) and T(B) = 1. That means that action 1 is taken when in state A, and the same action is taken when in sta
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