Steve, You are correct --- though the words like "induction", "abduction", and "analogy" are used in many AI systems, under the hood they are really deduction with minor variations.
For one thing, all non-deductive inference types are uncertain by definition, so as far as binary logic is used, you won't get them. In that sense, "Mathematical Induction" or "Induction/abduction by exhaustive enumeration" are all deductions. Even probabilistic inference can be purely deductive --- if all the inference start and end in the same (consistent) probabilistic distribution. Pei On Thu, Feb 14, 2008 at 12:14 PM, Stephen Reed <[EMAIL PROTECTED]> wrote: > > Pei, > Given your description, I agree B2 is the way to go. At Cycorp, the > inductive (e.g. rule induction), abductive (e.g. hypothesis generation), and > analogical reasoning engines I observed were all supported by deductive > inference. I also a member of a Cycorp team that collaborated with Pedro > Domingos' group at the university of Washington regarding probabilistic > reasoning. > > -Steve > Stephen L. Reed > > Artificial Intelligence Researcher > http://texai.org/blog > http://texai.org > 3008 Oak Crest Ave. > Austin, Texas, USA 78704 > 512.791.7860 > > > ----- Original Message ---- > From: Pei Wang <[EMAIL PROTECTED]> > To: agi@v2.listbox.com > Sent: Thursday, February 14, 2008 10:28:50 AM > Subject: [agi] reasoning & knowledge > > Steve, > > To me, the following two questions are independent of each other: > > *. What type of reasoning is needed for AI? The major answers are: > (A): deduction only, (B) multiple types, including deduction, > induction, abduction, analogy, etc. > > *. What type of knowledge should be reasoned upon? The major answers > are: (1) declarative only, (2) declarative and procedural. > > All four combination of the two answers are possible. Cyc is mainly > A1; you seem to suggest A2; in NARS it is B2. > > McDermott's paper has many good points, but his notion of "logic" and > "semantics" are too limited --- to what the "Logicist AI" has been > trying. > > As for Semantic Web and Ontology, I have no doubt that there are > useful for some special applications. However, from an AGI point of > view, their assumption about human knowledge is way to oversimplified. > I don't think the so-called "common knowledge" can be forced into the > rigid framework of "ontology", not to mention personal knowledge, > which is even more fluid. > > Even so, we can use SW as a possible knowledge source, and use > inference engine to reveal hidden conclusions in it, so SW is still > relevant to AGI. > > Pei > > > > > ________________________________ > Be a better friend, newshound, and know-it-all with Yahoo! Mobile. Try it > now. > ________________________________ > > agi | Archives | Modify Your Subscription ------------------------------------------- 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=95818715-a78a9b Powered by Listbox: http://www.listbox.com
