import tensorflow as tf

        t_params = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=self.name + '/target_net')
        e_params = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=self.name + '/eval_net')

        e_params += tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=self.name + '/mixing_net' + '/eval_hyper')
        t_params += tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=self.name + '/mixing_net' + '/target_hyper')

        with tf.variable_scope('soft_replacement'):
            self.target_replace_op = [tf.assign(t, e) for t, e in zip(t_params, e_params)]

        self.sess = tf.Session()
        self.sess.run(tf.global_variables_initializer())

