from player import Player
def partial_mcts(number_of_simulation, game_state):
return MonteCarloTreeSearch.get_best_move(game_state, number_of_simulation)
if __name__ == '__main__':
# https://docs.python.org/3/library/logging.html#levels
logging.basicConfig(format='%(message)s',
stream=sys.stdout,
level=logging.INFO)
simulation_count = 100
p1 = Player('P1', partial(partial_mcts, simulation_count))
p2 = Player('P2', lambda game_state: Minimax.get_best_move(game_state))
# p2 = Player('P2', lambda game_state: random.choice(game_state.get_valid_moves()))
players = [p1, p2]
board_size = 3
game = GameState(np.array([p1, p2]),
turn=1,
game_board=np.zeros((board_size, board_size)))
logging.debug(game)
i = 0
while not game.is_game_over:
player = players[i % 2]
logging.info(f'\n{player}\'s turn')
game = game.make_move(player.get_move(game))
print(game)
