import tensorflow as tf

            w_initializer, b_initializer = tf.random_normal_initializer(0., 0.1), tf.constant_initializer(0.0)

            # ------------------ build evaluate_net ------------------
            with tf.variable_scope('eval_net'):
                a_fc1 = tf.layers.dense(self.s, 128, tf.nn.relu, kernel_initializer=w_initializer,
                                        bias_initializer=b_initializer, name='agent_fc1_e')
                # a_fc2 = tf.layers.dense(a_fc1, 128, tf.nn.relu, kernel_initializer=w_initializer,
                #                         bias_initializer=b_initializer, name='agent_fc2_e')
                # a_fc3 = tf.layers.dense(a_fc2, 64, tf.nn.relu, kernel_initializer=w_initializer,
                #                         bias_initializer=b_initializer, name='agent_fc3_e')
                self.q_eval = tf.layers.dense(a_fc1, self.num_a, kernel_initializer=w_initializer,
                                              bias_initializer=b_initializer, name='q_e')

            # ------------------ build target_net ------------------
            with tf.variable_scope('target_net'):
                a_fc1_ = tf.layers.dense(self.s_, 128, tf.nn.relu, kernel_initializer=w_initializer,
                                         bias_initializer=b_initializer, name='agent_fc1_t')
                # a_fc2_ = tf.layers.dense(a_fc1_, 128, tf.nn.relu, kernel_initializer=w_initializer,
                #                          bias_initializer=b_initializer, name='agent_fc2_t')
                # a_fc3_ = tf.layers.dense(a_fc2_, 64, tf.nn.relu, kernel_initializer=w_initializer,
