Transferring knowledge across domains is one of the most fundamental problems
in machine learning, but doing so effectively in the context of reinforcement
learning remains largely an open problem. Current methods make strong
assumptions on the specifics of the task, often lack principled objectives, and
-- crucially -- modify individual policies, which migh