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:

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).