has the same expected gradient with respect to the parameters as the KL divergence data and the model does so its approximating maximum likelihood by using supervised learning to estimate a ratio that would be intractable if we were to evaluate the maximum likelihood criterion directly in general we can think of these different costs as being like reward functions we can kind of think of the generator net as being a reinforcement learning agent where it takes actions and we reward its actions depending on the way that the