Reinforcement Learning, Machine Learning, Monte Carlo Method, Temporal Difference, Data Science.
value of 0.5, which is higher than the true value of Nodes A and B. As the random policy makes a 50% chance of choosing a “wrong” step, which takes the agent away from the right terminal state, a higher α value will also emphasize the wrong steps and make the result away from the true value. Now