2008/11/29 Matt Mahoney <[EMAIL PROTECTED]>: > > The general problem of detecting overfitting is not computable. The principle > according to Occam's Razor, formalized and proven by Hutter's AIXI model, is > to choose the shortest program (simplest hypothesis) that generates the data. > Overfitting is the case of choosing a program that is too large.
Can someone explain AIXI to me? My understanding is that you've got some black-box process emitting output, and you generate all possible programs that emit the same output, then choose the shortest one. You then run this program and its subsequent output is what you predict the black-box process will do. This has the minor drawback, of course, that it requires infinite processing power and is therefore slightly impractical. I've read Hutter's paper "Universal algorithmic intelligence, A mathematical top->down approach" which amusingly describes itself as "a gentle introduction to the AIXI model". Hutter also describes AIXItl of computation time Ord(t*2^L) where I assume L is the length of the program and I'm not sure what t is. Is AIXItl something that could be practically written or is it purely a theoretical construct? In short, is there something to AIXI or is it something I can safely ignore? -- Philip Hunt, <[EMAIL PROTECTED]> Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html ------------------------------------------- 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
