|
Organizers |
Possibility Measures, Topology, and Quantitative Semantics
by
Michael Huth
Department of Computing and Information Sciences, Kansas State University
Coauthors: Reinhold Heckmann (Department of Computing and Information Sciences, Kansas State University)
Generalizing the usual predicate transformers to quantitative predicate transformers we uncover that such transformers have a mathematical dual which provides a mathematical foundation for possibility theories in Artificial Intelligence. This duality reveals formal analogies of quantitative predicates with continuous valuations. Three applications of this duality demonstrate its usefulness: we prove a universal property for the space of quantitative predicates, we characterize its inf-irreducible elements, and we show that bicontinuous lattices form a cartesian closed category.
Date received: June 26, 1997
Copyright © 1997 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # caao-29.