code for backpropagation part.

mctsagent.py

@staticmethod
def backup(node: Node, turn: int, outcome: int) -> None:
    """
    Update the node statistics on the path from the passed node to root to reflect
    the outcome of a randomly simulated playout.

    Args:
        node:
        turn: winner turn
        outcome: outcome of the rollout

    Returns:
        object:

    """
    # Careful: The reward is calculated for player who just played
    # at the node and not the next player to play
    reward = 0 if outcome == turn else 1

    while node is not None:
        node.N += 1
        node.Q += reward
        node = node.parent
        reward = 0 if reward == 1 else 1