Abstract
In this paper, we present techniques to support knowledge acquisition and validation within the framework of SGES. Our approach can be called a causal model-based knowledge acquisition process. It applies to a KBS composed of two knowledge bases: the expert knowledge base refering to the heuristic level is represented by production rules and will form the operational knowledge base, and the causal knowledge base composed of causal models. When new expert knowledge (a production rule) is acquired, abductive reasoning based on causal models provides justifications which are then analyzed with appropriate criteria. These justifications are useful for refining and extending an initial expert knowledge base: they can be used to propose explanations, to comment on rules, to control them, to suggest modifications or other rules. Our approach has been applied to the design of a medical diagnostic reasoning system for electromyography. Examples in this field are used in the paper.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Andreassen, S., Wolbye, M., Falck, B. & Andersen, S. (1987). Munin — a causal probabilistic network for interpretation of electromyographic findings. In Proceedings of the 10 th International Joint Conference on Artificial Intelligence (pp. 366–372). Milan, Italy.
Aussenac, N. (1989). A mediating representation to assist knowledge acquisition with MACAO. In J. H. Boose, B. R. Gaines & J. G. Ganascia, Eds., Proceedings of the 3 rd European Workshop on Knowledge Acquisition for Knowledge-Bas ed Systems (pp. 516–529). Paris, France.
Aussenac-Gilles, N., Krivine, J.-P. & Sallantin, J. (1992). Introduction to the special issue of knowledge acquisition. Revue d’Intelligence Artificielle, 6(1–2), 7–18. (In French).
Breuker, J., Wielinga, B., van Someren, M., de Hoog, R., Schreiber, G., de Greep, P., Bredeweg, B., Wielemaker, J. & Billault, J.-P. (1987). MUNIN — A Causal Probabilistic Network for Interpretation of Electromyographic Findings. Technical Report 1, University of Amsterdam and STL Ltd. Esprit Project P1098 Deliverable D1.
Bylander, T. & Chandrasekaran, B. (1987). Generic tasks for knowledge-based reasoning: the right level of abstraction for knowledge acquisition. International Journal of Man-Machine Studies, 26, 231–243.
Chandrasekaran, B. (1987). Towards a functional architecture for intelligence based on generic information processing tasks. In Proceedings of the 10 th International Joint Conference on Artificial Intelligence (pp. 1183–1192). Milan, Italy.
Chandrasekaran, B. & Mittal, S. (1983). Deep versus compiled knowledge approaches to diagnostic problem-solving. International Journal of Man-Machine Studies, 19, 425–436.
Charlet, J. (1993). ACTE: a causal model-based knowledge acquisition tool. In J.-M. David & J.-P. Krivine, Eds., Second Generation Expert Systems. Springer Verlag. In this book.
Charlet, J. & Gascuel, O. (1989). Knowledge acquisition by causal model and metaknowledge. In J. H. Boose, B. R. Gaines & J. G. Ganascia, Eds., Proceedings of the 3 rd European Workshop on Knowledge Acquisition for Knowledge-Based Systems (pp. 212–225). Paris, France.
Chittaro, L., Constantini, C., Giovanni, G., Carlo, T. & Topanno, E. (1989). Diagnosis based on cooperation of multiple knowledge sources. In Proceedings of the 9 th International Workshop Expert Systems & their Applications Avignon, France.
Clancey, W. (1981). The epistemology of a rule-based expert system: a framework for explanation. Artificial Intelligence, 27(3), 289–350.
Clancey, W. J. (1985). Heuristic Classification. Artificial Intelligence, 27(3), 289–350.
Console, L., Fossa, M. & Torasso, P. (1989a). Acquisition of causal knowledge in the check system. Computers and Artificial Intelligence, 8(4), 323–345.
Console, L., Fossa, M. & Torasso, P. (1989b). Heuristic and causal reasoning in check. In J. David, R. Huber, J. Krivine & C. Kulikowski, Eds., AI and Expert Systems in Scientific Computing: J.C. Baltzer Scientific Publ. Co.
Cordier, M.-O. & Reynaud, C. (1991). Knowledge acquisition techniques and second generation expert systems. Applied Artificial Intelligence, 5(3), 209–226.
David, J.-M. & Krwine, J.-P. (1989). Augmenting experience-based diagnosis with causal reasoning. Applied Artificial Intelligence, 3(2–3), 239–248.
Eshelman, L. (1988). MOLE: a knowledge acquisition tool for cover-and-differentiate systems. In S. Marcus, Ed., Automating Knowledge Acquisition for Expert Systems. Kluwer Academic Publishers.
Kahn, G., Nowlan, S. & McDermott, J. (1985). MORE: an intelligent knowledge acquisition tool. In A. Joshi, Ed., Proceedings of the 9 th International Joint Conference on Artificial Intelligence (pp. 581–585). Los Angeles, CA: M. Kaufmann, Inc.
Marcus, S. (1988). SALT: a knowledge acquisition tool for propose-and-revise systems. In S. Marcus, Ed., Automating Knowledge Acquisition for Expert Systems. Kluwer Academic Publishers.
Musen, M. (1989). Conceptuals models of interactive knowledge acquisition tools. Knowledge Acquisition, 1, 73–88.
Reynaud, C. (1989). ADELE, A Knowledge Acquisition Tool based on Justifications. PhD thesis, Université Paris Sud. (In French).
Reynaud, C. (1991). Where does knowledge acquisition interfere with explanation. In D. Herin-Aime, R. Dieng, J. Regoud & J. Angoujard, Eds., Proceedings of the 1 st conference on Knowledge Modeling & Expertise Transfer Sophia-Antipolis: IOS Press. (In French).
Steels, L. (1985). Second-generation expert systems. Journal of Future Generation Computer Science, 1(4).
Wielinga, B. & Breuker, J. (1985). KADS: Structured knowledge acquisition for expert systems. In Proceedings of the 5th International Workshop Expert Systems & their Applications Avignon, France.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1993 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Reynaud, C. (1993). Acquisition and Validation of Expert Knowledge by using Causal Models. In: David, JM., Krivine, JP., Simmons, R. (eds) Second Generation Expert Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77927-5_23
Download citation
DOI: https://doi.org/10.1007/978-3-642-77927-5_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-77929-9
Online ISBN: 978-3-642-77927-5
eBook Packages: Springer Book Archive