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. SSSEC(Motivation)

.QQ

We need a super-mathematics in which the operations are as unknown as
the quantities  they operate on, and  a super-mathematician, who does
not know what he is doing when he performs these operations.

-- Eddington

.ESS


Although the  motivation for  carrying out  this  research of  course
preceded the effort,  I have delayed until this  section a discussion
of why this is worthwhile, why it was attempted.

First  there  was  the  inherent  interest  of  getting  a handle  on
scientific creativity.    AM is  partly  a demonstration  that  some
aspects of  creative theory formation can be  demystified, can be
modelled as simple rule-governed behavior.

Related to this is the potential for learning from AM more about  the
processes of concept  formation. This was touched on  previously, and
several experiments already performed on AM will be detailed later.

Third, AM itself  may grow into something of pragmatic value. Perhaps
it will become a useful tool for mathematicians, for educators, or as
a  model for  similar systems in  more "practical"  fields.   Perhaps in  the
future we  scientists will be able to rely on automated assistants to
carry  out  the "hack"  phases  of  research,  the  tiresome  legwork
necessary for "secondary" creativity.

Historically, the  domain of AM came  from a search  for a scientific
field whose activities  had no  specific goal, and  in which  natural
language abilities were unnecessary.  This was to test out the BEINGs
[Lenat 75b]
ideas for a modular representation of knowledge.

It  would be  unfair not to  mention the  usual bad reasons  for this
research: the  "Look  ma, no  hands"  syndrome, the  AI  researcher's
classic maternal urges, ego, the usual thesis drives, etc.

.end;