On 25/03/2008, Vladimir Nesov <[EMAIL PROTECTED]> wrote > > Simple systems can be computationally universal, so it's not an issue > in itself. On the other hand, no learning algorithm is universal, > there are always distributions that given algorithms will learn > miserably. The problem is to find a learning algorithm/representation > that has the right kind of bias to implement human-like performance.
First a riddle: What can be all learning algorithms, but is none? I'd disagree. Okay simple systems can be computationally universal, but what does that really mean. Computational universality means to be able to represent any computable function, the range and domain of this function are assumed to be from the natural numbers to itself. Most AI formulations when they say that are computationally universal are only talking about function of F: I → O where I is the input and O is the output. These include the formulations of neural networks/GA etc that I have seen. However there are lots of interesting programs in computers that do not map the input to the output. Humans also do not just map the input to the output, we also think, ruminate, model and remember. This does not affect the range of functions from the input to the output, but it does change how quickly they can be moved between. What I am interested in is in systems where the ranges and domains of the functions are entities inside the system. That is the F: I → S, F: S → O, and F: S→ S are important and should be potentially computationally universal. Where S is the internal memory of the system. This allows the system to be all possible learning algorithms (although only one at any time), but also it is no algorithm (else F: I x S → S, would be fixed). General purpose desktop computers are these kinds of systems. If they weren't how else could we implement any type of learning system on them? Thus the answer to my riddle. The question I have been trying to answer precisely is how to govern these sorts of systems so they roughly do what you want, without you having to give precise instructions. Will Pearson ------------------------------------------- agi Archives: http://www.listbox.com/member/archive/303/=now RSS Feed: http://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: http://www.listbox.com/member/?member_id=8660244&id_secret=98558129-0bdb63 Powered by Listbox: http://www.listbox.com
