On Mon, Aug 27, 2012 at 9:12 PM, Ben Goertzel <[email protected]> wrote: > For domains in which one is concerned with recognizing large ensembles > of weak patterns, the language one uses to represent patterns can make > a big difference... > > Image analysis, genetic data analysis and financial prediction are > contexts in which I've found this to be the case > > In these settings, if one does pattern recognition via automated > program learning with an Occam bias, > the underlying language relative to which the Occam bias is expressed > makes a big difference...
Absolutely, but these overheads are not constants - the computational cost of a poor choice of representation language is typically exponential. > From a different direction, consider Hutter's proof that AIXI-tl is as > good as any other reinforcement learning system ... up to an arbitrary > constant. Well, much violence is being done to the word 'constant' in this case. Sure, f(N) is constant for a given N, but... :) ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/21088071-c97d2393 Modify Your Subscription: https://www.listbox.com/member/?member_id=21088071&id_secret=21088071-2484a968 Powered by Listbox: http://www.listbox.com
