empirical studies

Our approach enables efficient optimization and sharing across modules. R1:"motivate their work very well, is technical sound," R2:"idea seems to be new," R3:"very important problem, better We will address reviewers' comments as follows. Theoretical grounding: the paper is not well grounded in neural network theory. R2 also asks "Why a dot product for the weighting?" But weighting itself indicates multiplication. R2 has not provided an alternative way for weighting. Meta-learning is attracting, Comparison to state-of-the-art (e.g. R2 also has not provided a reference on multi-task RL for us to compare. How to adopt it in multi-task RL is an interesting direction to study, but it is out of the scope of our paper. While R2 complains about our writing, other reviewers all have positive feedback: "I liked to read the paper, For the routing network, the inputs are the same as the policy including both states and task embedding.