Paper Info
Title
Semantic Verification of Rule-Based Systems with Arithmetic Constraints
Abstract
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.
Year
DOI
Venue
2000
10.1007/3-540-44469-6_41
DEXA
Keywords
Field
DocType
linear inequality,constraint logic programming,arithmetic constraints,production rule,initial fact base,semantic inconsistency,attribute value,semantic verification,atms-like theory,initial fb,arithmetic constraint,integrity constraint,rule-based systems,integrity constraints,rule based system
Information system,Data mining,Computer science,Theoretical computer science,Artificial intelligence,Constraint logic programming,Rule-based system,Knowledge representation and reasoning,Knowledge-based systems,Arithmetic,Data integrity,Linear inequality,Database
Conference
ISBN
Citations 
PageRank 
3-540-67978-2
10
0.65
References 
Authors
6
2
Name
Order
Citations
PageRank
Jaime Ramírez111416.36
Angélica de Antonio216127.23