Validation, verification and test of knowledge-based systems
Validation, verification and test of knowledge-based systems
Agile Development Of Diagnostic Knowledge Systems (Diski)
Agile Development Of Diagnostic Knowledge Systems (Diski)
Semi-automatic learning of simple diagnostic scores utilizing complexity measures
Artificial Intelligence in Medicine
OWL rules: A proposal and prototype implementation
Web Semantics: Science, Services and Agents on the World Wide Web
Rapid knowledge capture using subgroup discovery with incremental refinement
Proceedings of the 4th international conference on Knowledge capture
Knowledge-Based Systems
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Due to their simple and intuitive manner rules are often used for the implementation of intelligent systems. Besides general methods for the verification and validation of rule systems there exists only little research on the evaluation of their robustness with respect to faulty user inputs or partially incorrect rules. This paper introduces a gray box approach for testing the robustness of rule systems, thus including a preceding analysis of the utilized inputs and the application of background knowledge. The practicability of the approach is demonstrated by a case study.