Prototypes and production rules: an approach to knowledge representation for hypothesis formation

Abstract

A system called CENTAUR has been implemented to interpret data derived from pulmonary function tests using a knowledge representation that combines the advantages of both production rules and frames. The system uses a hypothesis-directed approach to problem solving, in which hypotheses are suggested by the Initial data, further Information is acquired, and then more specific hypotheses are selected. The hypotheses are represented as PROTOTYPES, frame-like data structures each of which characterizes some pulmonary disease. The prototypes guide the invocation of the production rules and focus the search for new information. Some of the advantages afforded by representing knowledge as both prototypes and rules are also presented.