TMLR paper accepted

David Kuric’s paper on learning re-useable options was accepted to TMLR. Paper, code, and video are available on OpenReview. It proposes a gradient-based meta learning approach to discover sub-policies that are useful for rapid adaptation to different MDPs in a family of tasks. Congrats, David!