1 Implement an exploring reinforcement learning agent that uses direct utility estimtion. Make two versions—one with a tabular representation and one using the function approximator in Equation (10). Compare their performance in three environments:

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a. The 43 world described in the chapter. b. A 10 x 10 world with no obstacles and a +1 reward at (10,10). c. A 10 x 10 world with no obstacles and a +1 reward at (5,5).