def expand_leaf(parent_node: MCTSNode, state, board):
""" Adds a new leaf to the tree by creating a new child node for the given node.
Args:
node: The node for which a child will be added.
state: The state of the game.
Returns: The added child node.
"""
# The parent node can execute all the actions in the current state
current_state = ravel_states(board, state, parent_node)
parent_node.untried_actions = board.legal_actions(current_state)
if len(parent_node.untried_actions) == 0:
print("Cant expand leaf there are no possıble plays proceed.")
parent_node.parent.wins = -inf
parent_node.wins = -inf
return None
#select a random action that can be executed in that node
#!!! Make this random. It is kinda random?
p_action = parent_node.untried_actions.pop()
#!!! action list might not be correct.
#create a new node which would be the next state as a result of the chosen action
new_node = MCTSNode(parent=parent_node,
parent_action=p_action,
action_list=parent_node.untried_actions)
parent_node.child_nodes[p_action] = new_node
return new_node
def backpropagate(added_node: MCTSNode, expectation):
""" Navigates the tree from a leaf node to the root, updating the win and visit count of each node along the path.
Args:
node: A leaf node.
won: An indicator of whether the bot won or lost the game.
"""
added_node.wins = expectation
while added_node.parent:
if added_node.parent.wins < expectation:
added_node.parent.wins = expectation
added_node = added_node.parent