Ejemplo n.º 1
0
 def plan(self, board):
     time_when_planning_should_stop = time.time() * 1000 + 250
     model_agent, transient_agent = self.initialize_planning_phase()
     while time.time() * 1000 < time_when_planning_should_stop:
         copy_of_board = copy.deepcopy(board)
         game = Backgammon()
         game.reset()
         game.set_player_1(model_agent)
         game.set_player_2(transient_agent)
         reward = game.play(start_with_this_board=copy_of_board)
         transient_agent.add_reward(reward)
Ejemplo n.º 2
0
def nn_vs_nn_export_better_player():
    player1 = NNAgent1(verbose = True)
    player2 = NNAgent1(load_best=True)

    stats = Statistic(player1, verbose=True)

    while True:
        bg = Backgammon()
        bg.set_player_1(player1)
        bg.set_player_2(player2)
        winner = bg.play()

        player1.add_reward(winner)
        player2.add_reward(-1 * winner)

        stats.add_win(winner)

        if stats.nn_is_better() and stats.games_played % 100 == 0:
            break

    # only way to reach this point is if the current
    # neural network is better than the BestNNAgent()
    # ... at least I think so
    # thus, we export the current as best
    print("Congratulations, you brought the network one step closer")
    print("to taking over the world (of backgammon)!!!")
    player1.export_model(filename="nn_best_model")
Ejemplo n.º 3
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def do_default():
    """
    Play with a neural network against random
    """
    player1 = get_agent_by_config_name('nn_pg_2', 'best')
    player2 = get_agent_by_config_name('random', 'None')

    player1.training = True
    player2.training = True

    stats = Statistic(player1, verbose=True)

    # play games forever
    while True:

        bg = Backgammon()
        bg.set_player_1(player1)
        bg.set_player_2(player2)
        winner = bg.play()

        player1.add_reward(winner)
        player2.add_reward(-winner)

        # Reward the neural network agent
        # player1.reward_player(winner)

        stats.add_win(winner)
Ejemplo n.º 4
0
def train(competitors):
    # Train
    print("Training...")
    iteration = 0
    while True:
        iteration += 1
        competitor1, competitor2 = random_pair_not_self(competitors)

        player1 = competitor1['agent']
        player2 = competitor2['agent']

        player1.training = True
        player2.training = True

        bg = Backgammon()
        bg.set_player_1(player1)
        bg.set_player_2(player2)

        # 1 if player 1 won, -1 if player 2 won
        result = bg.play()

        player1.add_reward(result)
        player2.add_reward(-result)
        update_wins_and_losses(result, competitor1, competitor2)

        # Rate performance
        competitor1['rating'], competitor2['rating'] = update_rating(
            competitor1['rating'], competitor2['rating'], result)

        if iteration % 10 == 0:
            print_competitors(competitors, iteration)

        if iteration % (100 * len(competitors)) == 0:
            save_competitors(competitors)
Ejemplo n.º 5
0
def self_play():
    """
    Makes a human agent play against another (or the same) human agent.
    """

    player1 = HumanAgent()
    player2 = HumanAgent()

    bg = Backgammon()
    bg.set_player_1(player1)
    bg.set_player_2(player2)
    bg.play()
Ejemplo n.º 6
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def test_play():
    """
    Makes a human agent play against another (or the same) human agent.
    """

    player1 = HumanAgent()
    player2 = get_agent_by_config_name('nn_pg', 'best')

    bg = Backgammon()
    bg.set_player_1(player1)
    bg.set_player_2(player2)
    bg.play()
Ejemplo n.º 7
0
def random_play():
    """
    Makes a random agent play against another random agent.
    """

    player1 = RandomAgent()
    player2 = RandomAgent()

    bg = Backgammon()
    bg.set_player_1(player1)
    bg.set_player_2(player2)
    bg.play(commentary=True, verbose=True)
Ejemplo n.º 8
0
    def action(self, board, dice, player):
        """
        Args:
            board (ndarray): backgammon board
            dice (ndarray): a pair of dice
            player: the number for the player on the board who's turn it is.

        Returns:
            A move `move`.
        """

        move = []
        possible_moves, possible_boards = Backgammon.get_all_legal_moves_for_two_dice(
            board, dice)

        if len(possible_moves) != 0:
            move = self.pub_stomper_policy(possible_moves, possible_boards,
                                           dice, board)

        return move
Ejemplo n.º 9
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    def action(self, board, dice, player):
        """
        Args:
            board (ndarray): backgammon board
            dice (ndarray): a pair of dice
            player: the number for the player on the board who's turn it is.

        Returns:
            A move `move`.
        """

        # check out the legal moves available for dice throw
        move = []
        possible_moves, _ = Backgammon.get_all_legal_moves_for_two_dice(
            board, dice)

        if len(possible_moves) == 0:
            return []
        else:
            move = possible_moves[np.random.randint(len(possible_moves))]

        return move
Ejemplo n.º 10
0
    def action(self, board, dice, player):
        """
        Args:
            board (ndarray): backgammon board
            dice (ndarray): a pair of dice
            player: the number for the player on the board who's turn it is.

        Returns:
            A move `move`.
        """

        all_legal_moves = Backgammon.get_all_legal_moves_for_two_dice(
            board, dice)[0]

        # Runs this until a legal move is made.
        while True:

            print(Backgammon.to_string(board))
            print("")
            print("   You: " + str(Backgammon.get_player_symbol(player)))
            print("   Dice: " + str(dice))
            print("")
            print("    Press (enter) to pass if no moves are possible.")
            print("    Syntax: POSITION_FROM POSITION_TO")

            if len(all_legal_moves) == 0:
                # No possible moves
                print("No possible moves.  Press (enter) to continue.")
                input("Input: ")
                return []
            else:
                # Some moves possible
                move_1 = parse_input(input("Input: "))

                valid_move_1 = False

                future_legal_moves = []

                for moves in all_legal_moves:
                    if len(moves) > 0:
                        first_move = moves[0]
                        if len(first_move) == 2:
                            if first_move[0] == move_1[0] and first_move[
                                    1] == move_1[1]:
                                valid_move_1 = True
                                future_legal_moves += [moves[1]]

                if valid_move_1:
                    # Check if future moves are possible
                    if len(future_legal_moves) == 0:
                        return [move_1]
                    else:
                        move_2 = parse_input(input("Input: "))

                        for second_move in future_legal_moves:
                            if second_move[0] == move_2[0] and second_move[
                                    1] == move_2[1]:
                                return [move_1, move_2]

                        print("Invalid second move")
                else:
                    print("Invalid move")