Building expert systems
Case-based reasoning
Knowledge reuse among diagnostic problem-solving methods in the shell-kit D3
International Journal of Human-Computer Studies
Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
Binary vs. non-binary constraints
Artificial Intelligence
Knowledge-Based Scheduling Systems in Industry and Medicine
IEEE Expert: Intelligent Systems and Their Applications
What Are Ontologies, and Why Do We Need Them?
IEEE Intelligent Systems
The Difference All-Difference Makes
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
An Open-Ended Finite Domain Constraint Solver
PLILP '97 Proceedings of the9th International Symposium on Programming Languages: Implementations, Logics, and Programs: Including a Special Trach on Declarative Programming Languages in Education
Using Prior Knowledge: Problems and Solutions
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The evolution of Protégé: an environment for knowledge-based systems development
International Journal of Human-Computer Studies
Meta-knowledge in systems design: panacea … or undelivered promise?
The Knowledge Engineering Review
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
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Effective reuse of Knowledge Bases (KBs) often entails the expensive task of identifying plausible KB-PS (Problem Solver) combinations. We propose a novel technique based on Constraint Satisfaction to enable more rapid identification of incompatible KBs, leaving fewer combinations on which to conduct a thorough investigation. In this paper, we describe our investigation process, its tools, and the latest empirical results applied to non-binary problems that demonstrate our relaxation approach is an effective method for plausibility testing.