--- Richard Loosemore <[EMAIL PROTECTED]> wrote: > Matt Mahoney wrote: > > --- Stan Nilsen <[EMAIL PROTECTED]> wrote: > > > >> Matt, > >> > >> Thanks for the links sent earlier. I especially like the paper by Legg > >> and Hutter regarding measurement of machine intelligence. The other > >> paper I find difficult, probably it's deeper than I am. > > > > The AIXI paper is essentially a proof of Occam's Razor. The proof uses a > > formal model of an agent and an environment as a pair of interacting > Turing > > machines exchanging symbols. In addition, at each step the environment > also > > sends a "reward" signal to the agent. The goal of the agent is to > maximize > > the accumulated reward. Hutter proves that if the environment is > computable > > or has a computable probability distribution, then the optimal behavior of > the > > agent is to guess at each step that the environment is simulated by the > > shortest program consistent with all of the interaction observed so far. > This > > optimal behavior is not computable in general, which means there is no > upper > > bound on intelligence. > > Nonsense. None of this follows from the AIXI paper. I have explained > why several times in the past, but since you keep repeating these kinds > of declarations about it, I feel obliged to repeat that these assertions > are speculative extrapolations that are completeley unjustified by the > paper's actual content.
Yes it does. Hutter proved that the optimal behavior of an agent in a Solomonoff distribution of environments is not computable. If it was computable, then there would be a finite solution that was maximally intelligent according to Hutter and Legg's definition of universal intelligence. -- Matt Mahoney, [EMAIL PROTECTED] ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=8660244&id_secret=78395068-9af1e2
