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. -------