Before revision:  Its costly generation can be amortized by training dense agents with low-dimensional input and thereby at lower computational cost .
After revision:  Finally, we propose a simple initialization rescaling which promotes the robust identification of sparse task representations in low-dimensional input and thereby at lower computational cost .