A Description Classifier for the Predicate Calculus
Robert M. MacGregor
USC/Information Sciences Institute
4676 Admiralty Way
Marina del Rey, CA 90292
[email protected]
Abstract
A description classifier organizes concepts and relations into a
taxonomy based on the results of subsumption computations applied to
pairs of relation definitions. Until now, description classifiers have
only been designed to operate over definitions phrased in highly
restricted subsets of the predicate calculus. This paper describes a
classifier able to reason with definitions phrased in the full first
order predicate calculus, extended with sets, cardinality, equality,
scalar inequalities, and predicate variables. The performance of the
new classifier is comparable to that of existing description
classifiers. Our classifier introduces two new techniques, dual
representations and auto-Socratic elaboration, that may be expected to
improve the performance of existing description classifiers.
in Proceedings of the Twelfth National Conference on Artificial
Intelligence, (AAAI 94), pp. 213-220, 1994.
The full paper is available in postscript. Get Postscript. (8pp)
Back to Paper List