1) This is an interesting approach. It looks very similar to the approach taken by the mid-20th century cybernetics movement—namely, modeling social and cognitive feedback processes with the metaphors of electrical engineering. Based on this response, you in particular might be interested in the history of that intellectual movement.
My problem with this approach is that it considers the optimization process as a black box. That seems particularly unhelpful when we are talking about the optimization process acting on itself as a cognitive process. It’s easy to imagine that such a thing could just turn itself into a superoptimizer, but that would not be taking into account what we know about computational complexity.
I think that it’s this kind of metaphor that is responsible for “foom” intuitions, but I think those are misplaced.
2) Partial differential equations assume continuous functions, no? But in computation, we are dealing almost always with discrete math. What do you think about using concepts from combinatorial optimization theory, since those are already designed to deal with things like optimization resources and optimization efficiency?
Thanks. That’s very helpful.
I’ve been thinking about Stuart Russell lately, which reminds me...bounded rationality. Isn’t there a bunch of literature on that?
http://en.wikipedia.org/wiki/Bounded_rationality
Have you ever looked into any connections there? Any luck with that?