def agent_start(self, observation):
		screen = observation.intArray[128:]
		screen = np.reshape(screen, (210, -1))
		maze = detect_maze(screen)
		self.image = pacman_image(maze)
		return_action = Action()
		action = randrange(self.numActions)
		return_action.intArray = [action]
		self.lastAction = copy.deepcopy(return_action)
		self.lastObservation = copy.deepcopy(observation)

		return return_action
    pygame.init()
    ale.setBool('sound', False) # Sound doesn't work on OSX
  elif sys.platform.startswith('linux'):
    ale.setBool('sound', True)
  ale.setBool('display_screen', True)

# Load the ROM file
ale.loadROM(sys.argv[1])

# Get the list of legal actions
legal_actions = ale.getLegalActionSet()

# Play 10 episodes
screen = np.reshape(ale.getScreen(), (210, -1))
maze = detect_maze(screen)
image = pacman_image(maze)
# print_maze(maze)

for episode in xrange(1):
  total_reward = 0
  step = 1
  while not ale.game_over():
    # if step == 500:
    screen = np.reshape(ale.getScreen(), (210, -1))
    if step % 3 == 0:
      image.new_image(screen)
    a = legal_actions[randrange(len(legal_actions))]
    step += 1
    # Apply an action and get the resulting reward
    reward = ale.act(a);
    total_reward += reward