On 23 Oct 2006 at 13:26, Ben Goertzel wrote: > Whereas, my view is that it is precisely the effective combination of > probabilistic logic with complex systems science (including the notion of > emergence) that will lead to, finally, a coherent and useful theoretical > framework for designing and analyzing AGI systems...
You know my position on 'complex systems science'; yet to do anything useful, unlikely to ever help in AGI, would create FAI-incompatible systems even if it could. We don't really care about the global dynamics of arbitrary distributed systems anyway. What we care about is finding systems that produce useful behaviour, where 'useful' consists of a description of what we want plus an explicit or implicit description of behaviour or outcomes that would be unacceptable. Creating a general theory of how optimisation pressure is exerted on outcome sets, through layered systems that implement progressive (mostly specialising) transforms, covers the same kind of ground but is much more useful (and hopefully a little easier, though by no means easy). > I am also interested in creating a fundamental theoretical framework for > AGI, but am pursuing this on the backburner in parallel with practical work > on Novamente (even tho I personally find theoretical work more fun...). I prefer practical work, but I've accepted that to have a nontrivial chance of success theory has to come first, and also that theory about what you want has to come before theory about how to get it. My single biggest disagreement with Eliezer is probably that I think it's possible to proceed with a description of how you will specify what you actually want, rather than an exact specification of what you want (i.e. that it's possible to design an AGI that is capable of implementing a range of goal systems, including the kind of Friendly goal systems that I hope will be invented). Thus I'm doing AGI design rather than researching Friendliness theory (though I /would/ be doing that if I was better equipped for it than AGI research). > I find that in working on the theoretical framework it is very helpful > to proceed in the context of a well-fleshed-out practical design... Our positions on experimental work are actually quite close, but still distinct in some important respects. For example, the likelihood of being able to extrapolate experimental results on goal system dynamics; at least these days you accept that any such extrapolation is futile without a deep and verifiable understanding of the underlying functional mechanisms. I mostly agree with Eliezer there in saying that if you had an adequate understanding for extrapolation the experiments would (probably) only be useful for additional confirmation, but conversely I do think experimentation has an important role in developing tractable algorithms. Michael Wilson Director of Research and Development Bitphase AI Ltd - http://www.bitphase.com ----- 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/[EMAIL PROTECTED]
