--- Shane Legg <[EMAIL PROTECTED]> wrote: > Matt, > > Shane Legg's definition of universal intelligence requires (I believe) > complexity but not adaptability. > > > In a universal intelligence test the agent never knows what the environment > it is facing is. It can only try to learn from experience and adapt in > order to > perform well. This means that a system which is not adaptive will have a > very low universal intelligence. Even within a single environment, some > environments will change over time and thus the agent must adapt in order > to keep performing well. > > Shane
I was thinking of your other paper, which showed that a Turing machine cannot learn to predict an environment of higher algorithmic complexity, thus the requirement of complexity. But I did not see any formal definition of "adaptability" or any requirement for it. An obvious counterexample would be AIXI. I realize that there are no known *efficient* intelligent systems that aren't adaptive, in the sense of being an iterative process of test and incremental update. Examples include evolution, the human brain, and software development. In another post I mentioned Kauffman's observation that complex systems tend to reside on the boundary between stability and chaos. I believe this is because stable systems are not complex and chaotic systems are not adaptive. -- 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=231415&user_secret=fabd7936
