tictactoe.py

from games.tictactoe import TicTacToeGame

#Returns -1 for loss, +1 for win, 0 for draw
def value(game):
    if game.over():
        return -game.score()
    
    state_values = []
    for move in game.valid_moves():
        game.make_move(move)
        # guaranteed win for P2 is loss for P1, so we flip values
        state_values.append(-value(game)) 
        game.undo_move()
	
    # The player always chooses the optimal game state
    # +1 (win) if possible, otherwise draw, then loss
    return max(state_values)

#Chooses optimal move to play
def ai_best_move(game):
	
    action_dict = {}
    for move in game.valid_moves():
        game.make_move(move)
        action_dict[move] = value(game)
        game.undo_move()

    return min(action_dict, key=action_dict.get)