Review for NeurIPS paper: Neural Dynamic Policies for End-to-End Sensorimotor Learning

Weaknesses: The biggest limitation is the lack of imitation learning experiments. The authors chose to conduct an imitation learning experiment in a digit writing domain. However, the authors ran extensive RL experiments in a variety of robotic manipulation domains - I strongly advise using a policy trained on these domains as an expert (preferably not trained with NDP) and running behavioral cloning experiments using NDP and comparing against other action spaces and policy architectures. This would help decouple the benefit of NDP for exploration from the benefit of NDP as an action representation for control and modeling action sequences and should be a fairly straightforward experiment to run. It would also be interesting to see the effect of the control frequency and subsampling expert action sequences in the data - something that NDP is uniquely suited to do.