Question 2: (10 Points) : Consider the coin game described in Lecture | in which there are 30 coins on a table. You and your opponent pick up 1, 2, or 3 coins each turn. You continue until the last coi is picked up. The player who picks up the last coin is the loser. Assume you go first and your opponent randomly selects 1, 2, or 3 coins with equal probability unless limited by the number of available coins (e.g., if the opponent decides to pick up 2 but only | remains, then the opponent picks up only | coin). Use Monte Carlo Policy Improvement to solve this problem. Explain the numerical parameters you used to find an optimal policy