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GENERAL LINE CONCERNING LIGHTHILL REPORT


1. Lighthill has  misunderstood AI.  Primarily he  doesn't understand
what  the  basic scientific  problems  are.   His  ABC classification
shows that  he regards the  basic research  part of  AI as  concerned
with  the   central  nervous   system  -  with   neurophysiology  and
psychology as he elaborates it.

2.  In  fact,  the  basic  research  part  of  AI  is  the  study  of
intellectual mechanisms abstracted from how they are  realized in the
human or animal.  This is partly for its own  sake and partly because
intellectual mechanisms  are  more accessible  by  studying  problems
than by studying physiology or the behavior of animals and people.

3.  The  experimental  study of  these  mechanisms  is  important  to
discover their nature.

4. However,  AI is in bad theoretical shape,  and there is no present
agreement on what the theory should be, although there is  now pretty
good agreement that  the main problem holding up progress  is that of
how  to represent  the kind  of partial  information about  the world
that everyone  knows and  how to  represent the  kind of  information
about the world we get through our senses.

The bad theoretical situation is perhaps one of the reasons outsiders
misunderstand the field.  It is especially easy for physical scientists
to misunderstand, because the things that might seem to work on the
basis of their experience do not in fact work.  Witness the lack of
success of those who have tried to apply information theory, etc.

5. Some evidence that Lighthill has misunderstood:

	a. He says that the  quality of a chess program is determined
by the quality of its evaluation  function.  This was the guess  that
Turing  and  Shannon  and  Bernstein   made,  but  the  disappointing
performance of Bernestein's  program showed that it is mistaken.  The
quality of a chess program is  more determined by its choice of  what
part  of  the move  tree  to  investigate.    It took  experiment  to
convince  people that this  is so.   The parts of the  game where the
evaluation function  is primary  such as  the opening  are the  parts
present  computer  programs  play best.    Where  they  fail is  when
successful play depends  on having  a chess idea  that dictates  what
lines are to be  investigated in determining whether this  idea leads
to an  advantage.  We can get much better  chess programs when we can
formulate what  a chess idea  is and  can first  tell programs  chess
ideas  and then  have programs  generate chess  ideas.   Whether this
will happen in time to beat David Levy in 1978 now appears doubtful.

	b.  It  took  the  robot  projects  to  kill the  statistical
pattern  recognition and  perceptron  approaches  to vision.    These
approaches were  concerned with classifying  a pattern into  one of a
finite number of categories.   The approach doesn't  work at all  for
getting the visual information required  for manipulation or driving.
Perhaps  what  is   now  known  about  description  could  have  been
determined without manipulation-oriented  experiments.   In fact,  it
wasn't.