コード例 #1
0
 def expand(n):
     """expand the leaf node by adding all its children states"""
     if not n.children and not game.terminal_test(n.state):
         n.children = {
             MCT_Node(state=game.result(n.state, action), parent=n): action
             for action in game.actions(n.state)
         }
     return select(n)
コード例 #2
0
def monte_carlo_tree_search(state, game, N=1000):
    def select(n):
        """select a leaf node in the tree"""
        if n.children:
            return select(max(n.children.keys(), key=ucb))
        else:
            return n

    def expand(n):
        """expand the leaf node by adding all its children states"""
        if not n.children and not game.terminal_test(n.state):
            n.children = {
                MCT_Node(state=game.result(n.state, action), parent=n): action
                for action in game.actions(n.state)
            }
        return select(n)

    def simulate(game, state):
        """simulate the utility of current state by random picking a step"""
        player = game.to_move(state)
        while not game.terminal_test(state):
            action = random.choice(list(game.actions(state)))
            state = game.result(state, action)
        v = game.utility(state, player)
        return -v

    def backprop(n, utility):
        """passing the utility back to all parent nodes"""
        if utility > 0:
            n.U += utility
        # if utility == 0:
        #     n.U += 0.5
        n.N += 1
        if n.parent:
            backprop(n.parent, -utility)

    root = MCT_Node(state=state)

    for _ in range(N):
        leaf = select(root)
        child = expand(leaf)
        result = simulate(game, child.state)
        backprop(child, result)

    max_state = max(root.children, key=lambda p: p.N)

    return root.children.get(max_state)