Semantic Verification of Rule-Based Systems with Arithmetic Constraints
The aim of this paper is to show a method that is able to detect a particular class of semantic inconsistencies in a rule-based system (RBS). A semantic inconsistency is defined by an integrity constraint. A RBS verified by this method contains a set of production rules, and each production rule comprises a list of arithmetic constraints in its antecedent and a list of actions in its consequent. An arithmetic constraint is a linear inequality defined in the real domain that includes attributes, and an action is an assignment that changes an attribute value. As rules are allowed to include actions of this kind, the behaviour of the verified RBS is non-monotonic. The method is able to give a specification of all the initial fact bases (FB), and the rules from these initial FB that would have to be executed (in the right order) to cause an integrity constraint to be violated. So, the method builds an ATMS-like theory. Moreover, the treatment of arithmetic constraints is inspired by constraint logic programming.
Unable to display preview. Download preview PDF.
- 1.J. Clemente: “CRIB: Una herramienta para comprobación de restricciones en Sistemas Basados en el conocimiento”. Final-year project, Facultad de Informatica, Universidad Politécnica de Madrid, 1994.Google Scholar
- 2.M. S. Bazaraa, J.J. Jarvis, H. D. Sherali: “Linear Programming and Network Flows”. Ed. John Wiley Sons.Google Scholar
- 3.J. Cohen: “Constraint Logic Programming Languages”. Communications of the ACM. Vol. 33, No. 7. pp. 52–68.Google Scholar
- 4.J. De Kleer: “An Assumption Based TMS”. Artificial Intelligence 28, 1986.Google Scholar
- 5.A. Ginsberg. “Knowledge-Base Reduction: A New Approach to Checking Knowledge Bases for Inconsistency and Redundancy”. Proc. AAAI-88, pp. 585–589.Google Scholar
- 7.A.D. Preece: “Verification of rule-based expert systems in wide domains”. Research and Development in Expert Systems VI (Proc. Expert Systems 89), N. Shadbolt, Ed. Cambridge University Press, 1989, pp. 66–77.Google Scholar
- 8.J. Ramírez: “Diseño de una Herramienta para la Verificación Semántica de Bases de Conocimiento por Restricciones de Integridad”. Final-year project, Facultad de Informática, Universidad Politécnica de Madrid, 1996.Google Scholar
- 9.J. Ramírez, A. de Antonio: “MECORI: a Method for Knowledge Base Semantic Verification Based on Integrity Constraints”. Proceedings of the V&V Workshop at KR’98.Google Scholar
- 10.M. Rousset: “On the Consistency of Knowledge Bases: The COVADIS System”. Proceedings ECAI-88, Munich, Alemania, pp. 79–84.Google Scholar