Path: utzoo!attcan!uunet!ginosko!gem.mps.ohio-state.edu!tut.cis.ohio-state.edu!pt.cs.cmu.edu!andrew.cmu.edu!dg1v+ From: dg1v+@andrew.cmu.edu (David Greene) Newsgroups: comp.ai.neural-nets Subject: Re: Representational NN Message-ID: Date: 7 Oct 89 14:18:05 GMT References: <6403@watdcsu.waterloo.edu> <485@spinifex.eecs.unsw.oz> <1678@cs.yale.edu>, <708@ariel.unm.edu> Distribution: comp Organization: Graduate School of Industrial Administration, Carnegie Mellon, Pittsburgh, PA Lines: 37 In-Reply-To: <708@ariel.unm.edu> > Excerpts from netnews.comp.ai.neural-nets: 6-Oct-89 Re: Representational > NN william horne@wayback.un (2038) > I think that there are new concepts being offered that > are unique to connectionism, and that the consequences (if connectionism > is successful) is that we would see a paradigm shift away from logic > towards pattern recognition as the dominant mechanism of cognition. What do people out there think? I'm curious as to what the necessity of a "dominant mechanism" is... From the cog. psych literature, there seems to be favorable evidence of a "dual process" approach in cognition (such as by Posner or Kellog). This approach suggests that there are two levels, one being our conscious effort represented by "hypothesis testing" and the other being a sub-conscious process of "frequency sampling". Hypothesis testing fits into the frame of symbolic and logic processing while frequency sampling is associated with pattern-recognition approaches. Each area has its positive and negative qualities, but both perform essential functions in the human learning process. Why the frequent debate as to which is the "true path"? Although for a particular focus one might be provably superior, neither seems dominant, much less definitive. In fact, it would suggest that both approaches need to interact to form an effective "artificial intelligence". That interaction in the brain itself seems to be a ripe area of research. -David -------------------------------------------------------------------- David Perry Greene || ARPA: dg1v@andrew.cmu.edu GSIA /Robotics || dpg@isl1.ri.cmu.edu Carnegie Mellon Univ. || BITNET: dg1v%andrew@vb.cc.cmu.edu Pittsburgh, PA 15213 || UUCP: !harvard!andrew.cmu.edu!dg1v -------------------------------------------------------------------- "You're welcome to use my opinions, just don't get them all wrinkled."