gistfile1.txt

class DQNAgent:
    def __init__(self, name):
        with tf.variable_score(name):
            self.conv1 = Conv2D(32, 8, (4, 4), padding="same", activation="relu")
            self.pool1 = MaxPooling2D((2, 2))
            
            self.conv2 = Conv2D(64, 4, (2, 2), padding="same", activation="relu")
            self.pool2 = MaxPooling2D((2, 2))
            
            self.conv3 = Conv2D(64, 3, (1, 1), padding="same", activation"relu")
            self.pool3 = MaxPooling2D((2, 2))
            
            self.flatten = Flatten()
            self.fc1 = Dense(256, activation="relu")
            
            self.qvalues = Dense(ACTIONS)
        
            self.state = tf.placeholder("float", [None, 80, 80, 4])
            self.qvalues = self.get_symbolic_qvalues(self.state)
        
    def get_symbolic_qvalues(self, state_t):
        conv1 = self.conv1(state_t)
        pool1 = self.pool1(conv1)
        
        conv2 = self.conv2(pool1)
        pool2 = self.pool2(conv2)
        
        conv3 = self.conv3(pool2)
        pool3 = self.pool3(conv3)
        
        flatten = self.flatten(pool3)
        fc1 = self.fc1(flatten)
        
        return self.qvalues(fc1)