On Mon, Dec 1, 2008 at 8:04 PM, Matt Mahoney <[EMAIL PROTECTED]> wrote: > > The value of AIXI is not that it solves the general intelligence problem, but > rather > it explains why the problem is so hard.
It doesn't explain why it's hard (is impossible "hard"?). That you can't solve a problem exactly, doesn't mean that there is no simple satisfactory solution. > It also justifies a general principle that is > already used in science and in practical machine learning algorithms: > to choose the simplest hypothesis that fits the data. It formally defines > "simple" as the length of the shortest program that outputs a description > of the hypothesis. It's Solomonoff's universal induction, a much earlier result. Hutter generalized Solomonoff's induction to decision-making and proved some new results, but the idea of simple hypotheses prior and proof that it does good at learning are Solomonoff's. See ( http://www.scholarpedia.org/article/Algorithmic_probability ) for introduction. -- Vladimir Nesov [EMAIL PROTECTED] http://causalityrelay.wordpress.com/ ------------------------------------------- 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=120640061-aded06 Powered by Listbox: http://www.listbox.com
