For the environment to the right, the agent tried 6 episodesfrom the start state A to one of the ter

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For the environment to the right, the agent tried 6 episodesfrom the start state A to one of the terminal

states (C, D, and E), which are listed below: Episode #1: state = A, action = R, new state = C, reward =+10

Episode #2: state = A, action = L, new state = B, reward = 0

state = B, action = R, new state = E, reward = –1000

Episode #3: state = A, action = L, new state = B, reward = 0

state = B, action = L, new state = D, reward = +200

Episode #4: state = A, action = L, new state = B, reward = 0

state = B, action = R, new state = E, reward = –100

Episode #5: state = A, action = R, new state = C, reward =+25

Episode #6: state = A, action = L, new state = B, reward = 0

state = B, action = L, new state = D, reward = +400 Your task is to build the Q-table from these results. TheQ-table has two states and two actions per state. Use learning rate= 0.5 and discount factor = 1. All entries of the Q-table are zeroinitially. . . .

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