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Explanation as a Primary Task in Problem Solving

Published online by Cambridge University Press:  07 July 2009

Michael R. Wick
Michael R. Wick
Affiliation:
Computer Science Department, University of Wisconsin-Eau Claire, Eau Claire, WI 54702-4004, USA
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Abstract

This article summarizes the author's perspective on the discussions that occurred at the Workshop on Explanation and Problem Solving held during the Thirteenth International Joint Conference on Artificial Intelligence*. Motivated by those discussions, the article argues for the promotion of expert system explanation from a secondary task, used mainly for communication, to a primary task that is tightly integrated with the domain problem solving of the expert system.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 9 , Issue 1 , March 1994 , pp. 78 - 82
Copyright
Copyright © Cambridge University Press 1994

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References

Chandrasekaran, B, Tanner, M and Josephson, J, 1989. “Explaining control strategies in problem solving”. IEEE Expert 4 (1) 9–24.CrossRefGoogle Scholar
David, JM and Krivine, JP, 1989. “Augmenting experience-based diagnosis with causal reasoning”. Applied AI Journal.CrossRefGoogle Scholar
David, JM, Krivine, JP and Simmons, R (eds.), 1993. Second Generation Expert Systems. Berlin: Springer-Verlag.CrossRefGoogle Scholar
Hasling, D, Clancey, WJ and Rennels, G, 1984. “Strategic explanations for a diagnostic consultation system”. International Journal of Man–Machine Studies 20 3–19.CrossRefGoogle Scholar
Moore, J and Swartout, WR, 1989. “A reactive approach to explanation”. In: Proceedings of the Eleventh international Joint Conference on Artificial Intelligence.Google Scholar
Neches, R, Swartout, WR and Moore, JD, 1985. “Enhanced maintenance and explanation of expert system through explicit models of their development”. IEEE Transactions on Software Engineering 11(11) 1337–1351.CrossRefGoogle Scholar
Paris, CL, Wick, MR and Thompson, WB, 1988. “The line of reasoning versus the line of explanation”. In: Proceedings of the 1988 AAAI Workshop on Explanation, pp 4–7.Google Scholar
Ryan, J and Bridges, S, 1988. “Constructing explanations from Conceptual graphs”. In: Proceedings of the Third Annual Workshop on Conceptual Graphs.Google Scholar
Shortliffe, EH, 1976. Computer Based Medical Consultations: MYCIN. New York: Elsevierz/North Holland.Google Scholar
Swartout, WR, 1983. “XPLAIN: A system for creating and explaining expert consulting programs”. Artificial Intelligence 21 (3) 285–25.CrossRefGoogle Scholar
Tanner, MC and Josephson, JR, 1988. “Justifying diagnostic conclusions”. In: Proceedings of the 1988 AAAI Workshop on Explanation, pp 76–79.Google Scholar
Teach, RL and Shortliffe, EH, 1984. “An analysis of physician's attitudes”. In: Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Reading, MA: Addison-Wesley.Google Scholar
Wick, MR and Slagle, JR, 1989. “An explanation facility for today's expert systems”. IEEE Expert 4 (1) 26–36.CrossRefGoogle Scholar
Wick, MR and Thompson, WB, 1989. “Reconstructive explanation: Explanation as complex problem solving”. In: Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI).Google Scholar
Wick, MR and Thompson, WB, 1992. “Reconstructive expert system explanation”. Artificial intelligence 52 33–70.CrossRefGoogle Scholar
Wick, MR and Dieng, R, 1993. “The 1993 IJCAI Workshop on Explanation and Problem Solving”. Submitted to AI Magazine.Google Scholar