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Overview of current practice and research initiatives for the verification and validation of KBS

Published online by Cambridge University Press:  07 July 2009

T. J. Lydiard
Affiliation:
Artificial Intelligence Applications Institute, University of Edinburgh, Edinburgh, UK

Abstract

Based on a survey of recent literature, this report aims to highlight the issues associated with the verification and validation of knowledge based systems. The confusion arising from the lack of clear terminology is considered, along with some of the characteristics of knowledge based systems that cause particular difficulties for verification and validation. The various approaches that can be adopted to address these difficulties are discussed, followed by a survey of recent research initiatives.

The author concludes that many of the difficulties associated with the verification and validation of knowledge based systems are a feature of the complexity of the system being built and the manner of its development rather than of the specific technology chosen to implement it.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1992

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References

Born, G, 1988, “Guidelines for quality assurance of expert systemsCSA Working Group on QA and Expert Systems (1.1), 11.Google Scholar
Cragun, BJ and Steudel, HJ, 1987, “A decision-table-based processor for checking completeness and consistency in rule-based expert systemsInternational Journal of Man-Machine Studies 26 633648.Google Scholar
Enand, R, Kahn, GS and Mills, RA, 1990A methodology for validating large knowledge basesInternational Journal of Man-Machine Studies 33 361371.Google Scholar
Hoppe, T and Meseguer, P, 1991, “On the terminology of VVT” In: M. Grisoni, editor, Eurovav-91: Proceedings of the European Workshop on the Verification and Validation of Knowledge Based Systems pp 103108.Google Scholar
Inder, R and Filby, I, 1991, Survey of Knowledge Engineering Methods and Supporting Tools. Technical Report AIAI-TR-99, AIAI, December. (Also presented at the BCS SGES workshop on Knowledge-Based Systems Methodologies, 12 1991.Google Scholar
Johnson, RG, Joly, GC and King, PJH, 1987, Survey of Techniques for the Checking of Rule-Based Expert Systems. Technical report, Department of Computer Science, Birkbeck College, London.Google Scholar
Kang, Y and Bahill, AT, 1990, “A tool for detecting expert system errorsAI Expert 02, 4651.Google Scholar
Liu, NK and Dillon, T, 1991, “An approach towards the verification of expert systems using numerical Petri netsInternational Journal of Intelligent Systems 6 255276.Google Scholar
McGraw, KL and Harbison-Briggs, K, 1989, Knowledge Acquisition: Principles and Guidelines, pp 300325, Prentice-Hall.Google Scholar
Mengshoel, OJ, 1991, “KVAT: a tool for incremental knowledge validation in a knowledge engineering workbench: In: M. Grisoni, editor, Eurovav-91: Proceedings of the European Workshop on the Verification and Validation of Knowledge Based Systems pp 133146.Google Scholar
Nazareth, DL, 1989, “Issues in the verification of knowledge in rule-based systemsInternational Journal of Man-Machine Studies 30 255271.Google Scholar
Nazareth, DL and Kennedy, MH, 1991, “Verification of knowledge based systems using directed graphsKnowledge Acquisition 3 339360.Google Scholar
Nguyen, TA, “CHECK applied to ART” In: Third Conference on AI ApplicationsWashington, DC.Google Scholar
Nguyen, TA, Perkins, WA, Laffey, TJ and Pecora, D, 1987, “Knowledge base verificationAI Magazine 8(2) 6975, Summer.Google Scholar
O'Keefe, RM, Balci, O and Smith, EP, 1987, “Validating expert system performanceIEEE Expert, 8189, Winter.Google Scholar
Partridge, D, 1986, Artificial Intelligence: Applications in the Future of Software Development Engineering Ellis Horwood.Google Scholar
Pearce, D, 1991, “A model based approach to validation” In: M. Grisoni, editor, Eurovav-91: Proceedings of the European Workshop on the Verification and Validation of Knowledge Based Systems pp 5567.Google Scholar
Petitjean, S, Brunessaux, L and Vaudet, J-P, 1991, “Three pragmatic tools for the validation of knowledge based systems” In: M. Grisoni, editor, Eurovav-91: Proceedings of the European Workshop on the Verification and Validation of Knowledge Based Systems pp 111123.Google Scholar
Ribar, G, Arcoleo, Fand, Hollo, D, 1991, “Loan probe: testing a big expert systemAI Expert 4349, 05.Google Scholar
Stachowitz, RA, Chang, CL, Stock, TS and Combs, JB, 1987, “Building validation tools for knowledge based systems.” Proceedings of the SOAR Conference,Houston, TXNASA/JSC.Google Scholar
Stachowitz, RA, Combs, JB, 1987, “Validation of expert systems” In: Proceedings of the 20th Annual Hawaii International Conference on System Sciences.Google Scholar
van Someren, M, 1991, “Structural and formative validation of knowledge bases” In: M. Grisoni, editor, Eurovav-91: Proceedings of the European Workshop on the Verification and Validation of Knowledge Based Systems. pp 103108Google Scholar