On Thu, Sep 18, 2008 at 3:06 AM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > > Prolog is not fast, it is painfully slow for complex inferences due to using > backtracking as a control mechanism > > The time-complexity issue that matters for inference engines is > inference-control ... i.e. dampening the combinatorial explosion (which > backtracking does not do) > > Time-complexity issues within a single inference step can always be handled > via mathematical or code optimization, whereas optimizing inference control > is a deep, deep AI problem... > > So, actually, the main criterion for the AGI-friendliness of an inference > scheme is whether it lends itself to flexible, adaptive control via > > -- taking long-term, cross-problem inference history into account > > -- learning appropriately from noninferential cognitive mechanisms (e.g. > attention allocation...)
(I've been busy implementing my AGI in Lisp recently...) I think optimization of single inference steps and using global heuristics are both important. Prolog uses backtracking, but in my system I use all sorts of search strategies, not to mention abduction and induction. Also, currently I'm using general resolution instead of SLD resolution, which is for Horn clauses only. But one problem I face is that when I want to deal with equalities I have to use paramodulation (or some similar trick). This makes things more complex and as you know, I don't like it! I wonder if PLN has a binary-logic subset, or is every TV probabilistic by default? If you have a binary logic subset, then how does that subset differ from classical logic? People have said many times that resolution is inefficient, but I have never seen a theorem that says resolution is "slower" than other deduction methods such as natural deduction or tableaux. All such talk is based on anecdotal impressions. Also, I don't see why other deduction methods are that much different from resolution since their inference steps correspond to resolution steps very closely. Also, if you can apply heuristics in other deduction methods you can do the same with resolution. All in all, I see no reason why resolution is inferior. So I'm wondering if there are some novel way of doing binary that somehow makes inference faster than with classical logic. And exactly what is the price to be paid? What aspects of classical logic are lost? YKY ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
