> From: Matt Mahoney [mailto:[EMAIL PROTECTED] > > --- On Sun, 9/7/08, John G. Rose <[EMAIL PROTECTED]> wrote: > > > From: John G. Rose <[EMAIL PROTECTED]> > > Subject: RE: Language modeling (was Re: [agi] draft for comment) > > To: agi@v2.listbox.com > > Date: Sunday, September 7, 2008, 9:15 AM > > > From: Matt Mahoney [mailto:[EMAIL PROTECTED] > > > > > > --- On Sat, 9/6/08, John G. Rose > > <[EMAIL PROTECTED]> wrote: > > > > > > > Compression in itself has the overriding goal of > > reducing > > > > storage bits. > > > > > > Not the way I use it. The goal is to predict what the > > environment will > > > do next. Lossless compression is a way of measuring > > how well we are > > > doing. > > > > > > > Predicting the environment in order to determine which data > > to pack where, > > thus achieving higher compression ratio. Or compression as > > an integral part > > of prediction? Some types of prediction are inherently > > compressed I suppose. > > Predicting the environment to maximize reward. Hutter proved that > universal intelligence is a compression problem. The optimal behavior of > an AIXI agent is to guess the shortest program consistent with > observation so far. That's algorithmic compression. >
Oh I see. Guessing shortest program = compression. OK right. But yeah like Pei said the word "compression" is misleading. It implies a reduction where you are actually increasing understanding :) John ------------------------------------------- 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=111637683-c8fa51 Powered by Listbox: http://www.listbox.com
