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∂10-FEB-76  1250	DBL  	VISIT    
To:   DBL, JABARI @ MIT-AI, PHW @ MIT-AI   

Greetings,

I'll be arriving in Boston at 9:22am on Wed., Feb. 18.
I'd appreciate it if someone met me at the airport, but if
not I'll find my way to MIT. This process reverses at
9:50pm that night, when I fly to Newark. If someone will be
there, I'll mail you the airline name, etc.

So I'll only be there for Wednesday. I hope you can schedule a
colloquium (or at least raise a few interested souls for an informal
discussion session).

A nicely-pubbed abstract is winging its way toward you now; below is a
garbled version of it, in case you want to post the title or something.

Regards,
Doug Lenat

*********************************************************************
*********************************************************************


Automating the Discovery of Mathematical Concepts



We often face the difficult task of formulating new research problems
which must be soluble and yet  nontrivial.  Can such "originality" be
mechanized? Well, how about ⊗4partially⊗* mechanized?

This   talk  describes  one  approach  to  partially  automating  the
development of new mathematical concepts.  First, we  consider how to
⊗4explain⊗*  a discovery,  by  systematically analyzing  it  until it
seems obvious. Inverting this reduction procedure, we obtain a simple
scheme for ⊗4generating⊗* new discoveries.   Many heuristic rules are
needed  for guidance, to combat  the combinatorially explosive nature
of this process.

An experimental interactive  LISP program  has been developed,  which
carries out  some of the  activities involved in  simple mathematical
research:   noticing   obvious  relationships   in   empirical  data,
formulating new  definitions  out of  existing  ones, proposing  some
plausible conjectures, and estimating the potential worth of each new
concept.

After explaining the workings  of this program,  we can discuss  such
	issues as:
(i) Choice of task  domain: Why mathematics?  Suitability  of various
	other sciences.
(ii) Experiments one  can perform on this program: What do we hope to
	learn?
(iii) The role of the human user: spectator ⊗4vs⊗* co-researcher.
(iv) How can  one judge the performance  of a concept-proposer  which
	has no fixed goal?
(v) What kinds of discoveries are most difficult to mechanize?
(vi) Can the reasons for ⊗4considering⊗* X aid in ⊗4proving⊗* X?