def __init__(self, agent_filepath=""):
Player.__init__(self)
# Create the experience memory database
if not os.path.exists(REPLAY_MEMORY_FILENAME):
self.replay_memory = ReplayMemory()
else:
self.replay_memory = cPickle.load(open(REPLAY_MEMORY_FILENAME,
'r'))
# Initialize the convolutional neural network
self.network = MinecraftNet(agent_filepath)
self.ae_network = FeatureNet()
# Probability of selecting non-random action
self.epsilon = STARTING_EPSILON
# The total number of frames this agent has been trained on
# through all the minibatch training
self.frames_trained = 0
# Load old epsilon and frames learned values
self.load()
self.cnn_action_map = self.initActionMap()
# The current and previous sequences of game frames and actions
self.current_seq = None
self.previous_seq = None
self.previous_action = None
# Event logging
self.log = LogFile("run.log", True)
