there's some smoothness so once you've learned that we can space where there are smoothness you can optimize against that probably means that in that latent space distances are more meaningful I think now do reinforce learning against distances in that waking space you're doing it against the reward that's better that's not sparse but it's dense and it's giving a signal locally on whether you're improving or not improving on what you're doing and so we showed in a wide range of environments I did indeed reinforcement learning can be