Path: utzoo!attcan!uunet!know!zaphod.mps.ohio-state.edu!julius.cs.uiuc.edu!apple!well!nagle
From: nagle@well.sf.ca.us (John Nagle)
Newsgroups: comp.ai.philosophy
Subject: Re: Reasoning Paradigms
Message-ID: <21054@well.sf.ca.us>
Date: 7 Oct 90 03:35:21 GMT
References: <9963@ccncsu.ColoState.EDU> <3586@media-lab.MEDIA.MIT.EDU> <69347@lll-winken.LLNL.GOV> <3593@media-lab.MEDIA.MIT.EDU>
Lines: 31

minsky@media-lab.MEDIA.MIT.EDU (Marvin Minsky) writes:

>Is that bad?  Your locomotion system "learns" to walk, all right.  (It
>begins with an architecture of NN's that wonderfully work to adjust
>your reflexes.) 

      It is not clear that walking has to be learned.  The fact that
horses can stand within an hour of birth and run with the herd within
a day suggests otherwise.  The human developmental sequence may be
misleading here, humans being born in a less complete state than some
of the lower mammals.

>So may you can make a pretty good dog with NNs.  

      In our present state of ignorance, we would have difficulty making
a good ant with NNs.  The work of Rod Brooks and Patty Maes at MIT
shows that some simple locomotion problems can be dealt with in that way,
but full ant functionality has not been achieved.  Beer, Chiel, and
Sterling at CWRU are further along toward full insect functionality,
and, interestingly enough, their model of neural net components
resembles more closely the observed biological data, rather than
following the connectionist backward propagation approach.

     If you believe Sir John Eccles, all the mammals have roughly
the same brain architecture and the differences between the various
mammmals are quantitative, not qualitative.  Dissection, DNA distance,
and the evolutionary timetable all point in that direction.  So if we
can make it to dog-level AI, we should be almost there.  But we aren't
even close.  

					John Nagle