My hunch is that all probabilistic methods eventually degrade and they cannot capture "rules". Otherwise you would end up with a classical computer. I think what we are really looking for is a way to learn "rules" such that they remain stable over a certain number of iterations. Hopefully enough iterations to do useful work. Once you have a way to do this, you can extend the number of iterations by further imprinting on the system. The simplest example of this is if you have an oscillating signal whose amplitude is slowly decaying. A certain number of cycles will have an amplitude above a certain threshold that allows for useful work.