selection phase of mcts on the game.

mctsagent.py

def select_node(self) -> tuple:
    """
    Select a node in the tree to preform a single simulation from.

    """
    node = self.root
    state = deepcopy(self.root_state)

    # stop if we find reach a leaf node
    while len(node.children) != 0:
        # descend to the maximum value node, break ties at random
        children = node.children.values()
        max_value = max(children, key=lambda n: n.value).value
        max_nodes = [n for n in node.children.values()
                     if n.value == max_value]
        node = choice(max_nodes)
        state.play(node.move)

        # if some child node has not been explored select it before expanding
        # other children
        if node.N == 0:
            return node, state

    # if we reach a leaf node generate its children and return one of them
    # if the node is terminal, just return the terminal node
    if self.expand(node, state):
        node = choice(list(node.children.values()))
        state.play(node.move)
    return node, state

@staticmethod
def expand(parent: Node, state: GameState) -> bool:
    """
    Generate the children of the passed "parent" node based on the available
    moves in the passed gamestate and add them to the tree.

    Returns:
        bool: returns false If node is leaf (the game has ended).

    """
    children = []
    if state.winner != GameMeta.PLAYERS['none']:
        # game is over at this node so nothing to expand
        return False

    for move in state.moves():
        children.append(Node(move, parent))

    parent.add_children(children)
    return True