distinction was do we learn the weights of the policy network directly or do we learn the rules to update the weights now the question is whatever we learn how do we learn it and again we have to draw the distinction this time between i'm going to say classic or even though the terminology is not really correct classic rl and evolutionary methods okay so in classic rl what i would do is i would use my weights in order to obtain a reward and then i would update my weights so my delta w would be proportional to the gradient of w of the reward