MVILAIN@G.BBN.COM (Marc Vilain) (04/09/88)
BBN Science Development Program
AI Seminar Series Lecture
REPRESENTATION DESIGN FOR PROBLEM SOLVING
Jeffrey Van Baalen
MIT AI Laboratory
(jvb@HT.AI.MIT.EDU)
BBN Labs
10 Moulton Street
2nd floor large conference room
10:30 am, Thursday April 14
It has long been acknowledged that having a good representation is key
in effective problem solving. But what is a ``good'' representation?
In this talk, I overview a theory of representation design for problem
solving that answers this question for a class of problems called
analytical reasoning problems. These problems are typically very
difficult for general problem solvers, like theorem provers, to solve.
Yet people solve them comparatively easily by designing a specialized
representation for each problem and using it to aid the solution
process. The theory is motivated, in large part, by observations of the
problem solving behavior of people.
The implementation based on this theory takes as input a straightforward
predicate calculus translation of the problem, gathers any necessary
additional information, decides what to represent and how, designs the
representations, creates a LISP program that uses those representations,
and runs the program to produce a solution. The specialized representation
created is a structure whose syntax captures the semantics of the problem
domain and whose behavior enforces those semantics.
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