It seems as if we are beginning to talk past eachother. I think the problem may be that we have different implicit conceptions of the sort of AI being constructed. My implicit conception is that of an optimization problem. The AI is given the challenge of formulating the best response to its input that it can muster within real-world time constraints. This in some sense always a search problem; it just might be "all heuristic", so that it doesn't look much like a search. In designing an AI, I am implicitly assuming that we have some exact definition of intelligence, so that we know what we are looking for. This makes the optimization problem well-defined: the search space is that of all possible responses to the input, and the utility function is our definition of intelligence. *Our* problem is to find (1) efficient optimal search strategies, and where that fails, (2) good heuristics.
I'll admit that the general Conway analogy applies, because we are looking for heuristics with the property of giving good answers most of the time, and the math is sufficiently complicated as to be intractable in most cases. But your more recent variation, where Conway goes amiss, does not seem to be analogous? On Tue, Jun 24, 2008 at 9:02 PM, Richard Loosemore <[EMAIL PROTECTED]> wrote: > Abram Demski wrote: >>>> >>>> I'm still not really satisfied, though, because I would personally >>>> stop at the stage when the heuristic started to get messy, and say, >>>> "The problem is starting to become AI-complete, so at this point I >>>> should include a meta-level search to find a good heuristic for me, >>>> rather than trying to hard-code one..." >>> >>> And at that point, your lab and my lab are essentially starting to do >>> the same thing. You need to start searching the space of possible >>> heuristics in a systematic way, rather than just pick a hunch and go >>> with it. >>> >>> The problem, though, is that you might already have gotten yourself into >>> a You Can't Get There By Starting From Here situation. Suppose your >>> choice of basic logical formalism, and knowledge representation format >>> (and the knowledge acquisition methods that MUST come along with that >>> formalism) has boxed you into a corner in which there does not exist any >>> choice of heuristic control mechanism that will get your system up into >>> human-level intelligence territory? >> >> If the underlying search space was sufficiently general, we are OK, >> there is no way to get boxed in except by the heuristic. > > Wait: we are not talking about the same thing here. > > Analogous situation. Imagine that John Horton Conway is trying to invent a > cellular automaton with particular characteristics - say, he has already > decided that the basic rules MUST show the global characteristic of having a > thing like a glider and a thing like a glider gun. (This is equivalent to > us saying that we want to build a system that has the particular > characteristics that we colloquially call 'intelligence', and we will do it > with a system that is complex). > > But now Conway boxes himself into a corner: he decides, a priori, that the > cellular automaton MUST have three sexes, instead of the two sexes that we > are familiar with in Game of Life. So three states for every cell. But now > (we will suppose, for the sake of the argument), it just happens to be the > case that there do not exist ANY 3-sex cellular automata in which there are > emergent patterns equivalent to the glider and glider gun. Now, alas, > Conway is up poop creek without an instrument of propulsion - he can search > through the entire space of 3-sex automata until the end of the universe, > and he will never build a system that satisfies his requirement. > > This is the boxed-in corner that I am talking about. We decide that > intelligence must be built with some choice of logical formalism, plus > heuristics, and we assume that we can always keep jiggling the heuristics > until the system as a whole shows a significant degree of intelligence. But > there is nothing in the world that says that this is possible. We could be > in exactly the same system as our hypothetical Conway, trying to find a > solution in a part of the space of all possible systems in which there do > not exist any solutions. > > The real killer is that, unlike the example you mention below, mathematics > cannot possibly tell you that this part of the space does not contain any > solutions. That is the whole point of complex systems, n'est pas? No > analysis will let you know what the global properties are without doing a > brute force exploration of (simulations of) the system. > > > Richard Loosemore > > > >> This is what the mathematics is good for. An experiment, I think, will >> not tell you this, since a formalism can cover almost everything but >> not everything. For example, is a given notation for functions >> Turing-complete, or merely primitive recursive? Primitive recursion is >> amazingly expressive, so I think it would be easy to be fooled. But a >> proof of Turing-completeness will suffice. > > > > > > ------------------------------------------- > agi > Archives: http://www.listbox.com/member/archive/303/=now > RSS Feed: http://www.listbox.com/member/archive/rss/303/ > Modify Your Subscription: > http://www.listbox.com/member/?&; > Powered by Listbox: http://www.listbox.com > ------------------------------------------- agi Archives: http://www.listbox.com/member/archive/303/=now RSS Feed: http://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: http://www.listbox.com/member/?member_id=8660244&id_secret=106510220-47b225 Powered by Listbox: http://www.listbox.com
