import tensorflow as tf

        return sess.run(self.value_estimate, { self.state: [state] })[0][0]

    def update(self, state, target, sess=None):
        sess = sess or tf.get_default_session()
        for st_idx in range(len(state)):
            state[st_idx]=featurize_state(state[st_idx]);
