Path: utzoo!utgpu!water!watmath!clyde!att!osu-cis!tut.cis.ohio-state.edu!bloom-beacon!GLACIER.STANFORD.EDU!jbn From: jbn@GLACIER.STANFORD.EDU (John B. Nagle) Newsgroups: comp.ai.digest Subject: Re: Newell's Knowledge Level Message-ID: <19880905045757.8.NICK@HOWARD-JOHNSONS.LCS.MIT.EDU> Date: 5 Sep 88 04:57:00 GMT Sender: daemon@bloom-beacon.MIT.EDU Organization: The Internet Lines: 34 Approved: ailist@ai.ai.mit.edu To: comp-ai-digest@decwrl.dec.com Path: labrea!glacier!jbn From: John B. Nagle Newsgroups: comp.ai.digest Subject: Re: Newell's Knowledge Level Date: Sat, 3 Sep 88 11:06 EDT References: <19880903034508.9.NICK@HOWARD-JOHNSONS.LCS.MIT.EDU> Reply-To: John B. Nagle Organization: Stanford University Lines: 22 Much the same idea has been referred to as "deep understanding" by the rule-based knowledge representation people. The term "deep structure" is sometimes used by those working on natural language understanding. In both cases, the limitations of the superficial representations in use today are being recognized. The remark "Mycin doesn't know about bacteria" dates from the previous decade, but is still applicable. Many critics of AI, from Weitzenbaum to Dreyfus, have noted this problem, which some refer to as the "knowledge representation problem". This is a key unsolved problem in AI. A recent posting here by McCarthy indicates that he considers it the key unsolved problem, and that effort should be directed toward the development of a formal language suitable for the representation of "deep understanding" of the real world. I have not heard of any system where "deep understanding" or "deep structure" or a "knowledge level" were implemented in any general way. In a very few systems, always ones where the underlying domain is formalizable, there is some notion of deep understanding. Eurisko (Lenat) comes close. When people use these terms, they are usually talking about the parts of the problem for which no useful approaches are known. John Nagle