Iclr Safe Slac
Our paper Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation was accepted to ICLR 2023.
We propose Safe SLAC, an algorithm that uses a stochastic latent variable model combined with a safety critic to address the problem of safe reinforcement learning in realistic, high-dimensional settings.
Big congratulations to Yannick Hogewind, who did this work as part of his ELLIS fellowship within our group, supervised by Thiago!