コード例 #1
0
def performance_test():
    """
    the performance test borrowed from
    http://www.codeskulptor.org/#user41_rAX7Nukse9WzOOV.py    
    """    
    time.time()
    start = time.time()
    provided.play_game(mc_move, NTRIALS, False)
    print str(provided.play_game)+":   \t" + str( (time.time() - start) )
コード例 #2
0
        mc_update_scores(scores, board1, player)
        num -= 1


    next_move = get_best_move(board, scores)

    return next_move
    
 



# Test game with the console or the GUI.
# Uncomment whichever you prefer.
# Both should be commented out when you submit for
# testing to save time.

provided.play_game(mc_move, NTRIALS, False)        
# poc_ttt_gui.run_gui(3, provided.PLAYERX, mc_move, NTRIALS, False)


#import user35_PIk21NjpAa_0 as tests

#tests.test_mc_trial(mc_trial)                                             # tests for mc_trial

#tests.test_mc_update_scores(mc_update_scores, MCMATCH, MCOTHER)           # tests for mc_update_scores

#tests.test_get_best_move(get_best_move)                                   # tests for get_best_move

#tests.test_mc_move(mc_move, NTRIALS)      
        if player == provided.PLAYERX:
            if score < result[0]:
                score = max(score, result[0])
                final_move = _move
        else:
            if score > result[0]:
                score = min(score, result[0])
                final_move = _move

    return score, final_move


def move_wrapper(board, player, trials):
    """
    Wrapper to allow the use of the same infrastructure that was used
    for Monte Carlo Tic-Tac-Toe.
    """

    move = mm_move(board, player)
    #assert move[1] != (-1, -1), "returned illegal move (-1, -1)"
    return move[1]


# Test game with the console or the GUI.
# Uncomment whichever you prefer.
# Both should be commented out when you submit for
# testing to save time.

provided.play_game(move_wrapper, 1, False)
#poc_ttt_gui.run_gui(3, provided.PLAYERO, move_wrapper, 1, False)
コード例 #4
0
    all_move =[]
    for each in board.get_empty_squares():
        temp = board.clone()
        temp.move(each[0], each[1], player)
      
        all_move.append([minmax(temp, provided.switch_player(player)), each]) 
        
    if player == provided.PLAYERX:
        all_move.sort(key = lambda x: x[0], reverse=True)
    else:
        all_move.sort(key = lambda x: x[0])
    
    return all_move[0][0], all_move[0][1]

def move_wrapper(board, player, trials):
    """
    Wrapper to allow the use of the same infrastructure that was used
    for Monte Carlo Tic-Tac-Toe.
    """
    move = mm_move(board, player)
    assert move[1] != (-1, -1), "returned illegal move (-1, -1)"
    return move[1]

# Test game with the console or the GUI.
# Uncomment whichever you prefer.
# Both should be commented out when you submit for
# testing to save time.

provided.play_game(move_wrapper, 1, False)        
poc_ttt_gui.run_gui(3, provided.PLAYERO, move_wrapper, 1, False)
        """
    dimension = board.get_dim()
    scores = [[0 for dummy in range(dimension)] for dummy in range(dimension)]
    
    for dummy in range(trials):
        board_copy = board.clone()
        mc_trial(board_copy, player)
        mc_update_scores(scores, board_copy, player)
    
    return get_best_move(board, scores)

# Test game with the console or the GUI Uncomment whichever
# you prefer. Both should be commented out when you submit
# for testing to save time.

provided.play_game(mc_move, NTRIALS, False)
poc_ttt_gui.run_gui(3, provided.PLAYERX, mc_move, NTRIALS, False)

# # Testing code
# test_game = provided.TTTBoard(3)
# test_dim = test_game.get_dim()
# test_scores = [[0 for emptycol in range(test_dim)]
# for emptyrow in range(test_dim)]

# # test mc_trial()
# mc_trial(test_game, provided.PLAYERX)
# print str(test_game)
# print "Winner:", test_game.check_win(), "\n"

# # test mc_update_scores
# mc_update_scores(test_scores, test_game, provided.PLAYERX)
コード例 #6
0
    return res


###Test game with the console or the GUI.
AI_VS_AI_GAMES = 20
winners = []
lookup = {provided.PLAYERX: "Monte carol", provided.PLAYERO: "minMax"}
win1 = 0
win2 = 0
tie = 0
a1_total_t = 0
a2_total_t = 0
for i in range(AI_VS_AI_GAMES):
    # two AI test
    print("test", i)
    winner, a1_time, a2_time = provided.play_game(mc_move, NTRIALS, minMaxMove,
                                                  DEPTH, False)
    a1_total_t += a1_time
    a2_total_t += a2_time
    if winner == provided.PLAYERX:
        win1 += 1
    elif winner == provided.PLAYERO:
        win2 += 1
    else:
        tie += 1
print("%d %d %d\n" % (win1, tie, win2))

# poc_ttt_gui.run_gui(3, provided.PLAYERX, mc_move, NTRIALS, False)

# just run minmax
# poc_ttt_gui.run_gui(3, provided.PLAYERX, minMaxMove, DEPTH, False)