2008/7/6 Abram Demski <[EMAIL PROTECTED]>: > In fact, adding hidden predicates and entities in the case of Markov > logic makes the space of models Turing-complete (and even bigger than > that if higher-order logic is used). But if I am not mistaken the > clustering used in the paper I refer to is not that powerful. So the > question is: is clustering in general powerful enough for AGI? Is it > fundamental to how minds can and should work? >
I would say very important, but not fundamental. Consider the square/rectangle problem. You are given a number of pairs of numbers and you want to somehow say that pairs with the same numbers are in one class (of squares) and pairs of different numbers are rectangles. Imagine you have to learn to eat squares but not rectangles. However most cluster methods, while they could represent the cluster of squares, would require a lot of samples to get a long thin cluster running up the x=y line. If there was another dimension called z which was 1 when x equalled y, clustering would be very easy. Where does z come from? And why not z = 1 if x-9 = y^2? Finding decent dimensions to cluster on is a tricky problem. So I think the process by which the dimensions of clustering problems are created is more fundamental than clustering itself. Will Pearson ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=106510220-47b225 Powered by Listbox: http://www.listbox.com
