Sparse linear system are normally solved by using solvers like MINRES, Conjugate gradient, GMRES.
Efficient preconditioning, i.e., finding a matrix P such that PAx = Pb is easier to solve then the original problem, can drastically reduce the computational effort to solve for x. However, preconditioning is normally problem specific and there is not ONE preconditioner that works well for every problem.
I thought this would be an interesting problem to apply RL, since there are certain norms (e.g. condition number of matrix PA) to measure if P is a good preconditioner, but I could not find any research in this field.
Is there a specific problem why RL could not be applied?