Knowledge-Based Expert Systems
Computer - IEEE Centennial: the state of computing
Communications of the ACM
Building expert systems
AI Magazine
International Journal of Man-Machine Studies
A Predicate-Transition Net Model for Parallel Interpretation of Logic Programs
IEEE Transactions on Software Engineering
Knowledge acquisition: principles and guidelines
Knowledge acquisition: principles and guidelines
Validation, verification and test of knowledge-based systems
Validation, verification and test of knowledge-based systems
Validating and Verifying Knowledge-Based Systems
Validating and Verifying Knowledge-Based Systems
Symbolic Logic and Mechanical Theorem Proving
Symbolic Logic and Mechanical Theorem Proving
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Principles of Expert Systems
Expert Systems: Principles and Programming
Expert Systems: Principles and Programming
Proceedings of an Advanced Course on Petri Nets: Central Models and Their Properties, Advances in Petri Nets 1986-Part I
Static analysis of intensional databases in U-Datalog (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Verification and Validation of Knowledge-Based Systems
IEEE Transactions on Knowledge and Data Engineering
A High-Level Petri Nets-Based Approach to Verifying Task Structures
IEEE Transactions on Knowledge and Data Engineering
Fuzzy Rule Base Systems Verification Using High-Level Petri Nets
IEEE Transactions on Knowledge and Data Engineering
A Fuzzy Petri Nets Based Mechanism for Fuzzy Rules Reasoning
COMPSAC '97 Proceedings of the 21st International Computer Software and Applications Conference
Rule Based Programming with Constraints and Strategies
Selected papers from the Joint ERCIM/Compulog Net Workshop on New Trends in Contraints
A formal modeling approach for supply chain event management
Decision Support Systems
Value-added treatment inference model for rule-based certainty knowledge
Expert Systems with Applications: An International Journal
Complementary utilities for UML an UP in information systems
EATIS '07 Proceedings of the 2007 Euro American conference on Telematics and information systems
Conflicting treatment model for certainty rule-based knowledge
Expert Systems with Applications: An International Journal
When Is Inconsistency Considered Harmful: Temporal Characterization of Knowledge Base Inconsistency
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
On Temporal Properties of Knowledge Base Inconsistency
Transactions on Computational Science V
Model checking correctness properties of a middleware service for contract compliance
Proceedings of the 4th International Workshop on Middleware for Service Oriented Computing
Inconsistency: the good, the bad, and the ugly
IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
Quantifying knowledge base inconsistency via fixpoint semantics
Transactions on computational science II
Detecting redundant production rules
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Business process lines and decision tables driving flexibility by selection
SC'12 Proceedings of the 11th international conference on Software Composition
Resolving anomalies in configuration knowledge bases
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
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The knowledge base is the most important component in a knowledge-based system. Because a knowledge base is often built in an incremental, piecemeal fashion, potential errors may be inadvertently brought into it. One of the critical issues in developing reliable knowledge-based systems is how to verify the correctness of a knowledge base. The paper describes an automated tool called PREPARE for detecting potential errors in a knowledge base. PREPARE is based on modeling a knowledge base by using a predicate/transition net representation. Inconsistent, redundant, subsumed, circular, and incomplete rules in a knowledge base are then defined as patterns of the predicate/transition net model, and are detected through a syntactic pattern recognition method. The research results to date have indicated that: the methodology ran be adopted in knowledge-based systems where logic is used as knowledge representation formalism; the tool can be invoked at any stage of the system's development, even without a fully functioning inference engine; the predicate/transition net model of knowledge bases is easy to implement and provides a clear and understandable display of the knowledge to be used by the system.