Reviews: Successor Features for Transfer in Reinforcement Learning

This paper presents a RL optimization scheme and a theoretical analysis of its transfer performance. While the components of this work aren't novel, it combines them in an interesting, well-presented way that sheds new light. The definition of transfer given in Lines 89–91 is nonstandard. It seems to be missing the assumption that t is not in T. The role of T' is a bit strange, making this a requirement for "additional transfer" rather than just transfer. It should be better clarified that this is a stronger requirement than transfer, and explained what it's good for -- the paper shows this stronger property holds, but never uses it.