Communications of the ACM
AI Magazine
International Journal of Man-Machine Studies
AI Expert
Issues in the verification of knowledge in rule-based systems
International Journal of Man-Machine Studies
Well-structured knowledge bases
AI Expert
Knowledge-based systems: the view in 1986
AI in the 1980s and beyond
A Petri-Net based approach for verifying the integrity of production systems
International Journal of Man-Machine Studies
A new approach to detecting missing knowledge in expert system rule bases
International Journal of Man-Machine Studies
Verification of knowledge base redundancy and subsumption using graph transformations
International Journal of Expert Systems - Special issue on verification and validation (Part 2)
Intelligent Systems for Business: Expert Systems with Neural Networks
Intelligent Systems for Business: Expert Systems with Neural Networks
Introduction to Expert Systems
Introduction to Expert Systems
Investigating the Applicability of Petri Nets for Rule-Based System Verification
IEEE Transactions on Knowledge and Data Engineering
Fuzzy Rule Base Systems Verification Using High-Level Petri Nets
IEEE Transactions on Knowledge and Data Engineering
Ontology-based knowledge fusion framework using graph partitioning
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
Fuzzy Metagraph and Its Combination with the Indexing Approach in Rule-Based Systems
IEEE Transactions on Knowledge and Data Engineering
Checking the consistency of a hybrid knowledge base system
Knowledge-Based Systems
A schema to determine basketball defense strategies using a fuzzy expert system
FS'06 Proceedings of the 7th WSEAS International Conference on Fuzzy Systems
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Rule-based representation techniques have become popular for storage and manipulation of domain knowledge in expert systems. It is important that systems using such a representation are verified for accuracy before implementation. In recent years, graphical techniques have been found to provide a good framework for the detection of errors that may appear in a rule base [1], [16], [17], [19], [23]. In this work we present a graphical representation scheme that: 1) captures complex dependencies across clauses in a rule base in a compact yet intuitively clear manner and 2) is easily automated to detect structural errors in a rigorous fashion. Our technique uses a directed hypergraph to accurately detect the different types of structural errors that appear in a rule base. The technique allows rules to be represented in a manner that clearly identifies complex dependencies across compound clauses. Subsequently, the verification procedure can detect errors in an accurate fashion by using simple operations on the adjacency matrix of the directed hypergraph. The technique is shown to have a computational complexity that is comparable to that of other graphical techniques. The graphical representation coupled with the associated matrix operations illustrate how directed hypergraphs are a very appropriate representation technique for the verification task.