ActorNetwork.py 文件源码

def __init__(self, sess, state_size, action_size, BATCH_SIZE, TAU, LEARNING_RATE):
        self.sess = sess
        self.BATCH_SIZE = BATCH_SIZE
        self.TAU = TAU
        self.LEARNING_RATE = LEARNING_RATE

        K.set_session(sess)

        #Now create the model
        self.model , self.weights, self.state = self.create_actor_network(state_size, action_size)   
        self.target_model, self.target_weights, self.target_state = self.create_actor_network(state_size, action_size) 
        self.action_gradient = tf.placeholder(tf.float32,[None, action_size])
        self.params_grad = tf.gradients(self.model.output, self.weights, -self.action_gradient)
        grads = zip(self.params_grad, self.weights)
        self.optimize = tf.train.AdamOptimizer(LEARNING_RATE).apply_gradients(grads)
        self.sess.run(tf.global_variables_initializer())