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An answer to commentators on the paper “Generic tasks as building blocks for knowledge-based systems: the diagnosis and routine design examples”

Published online by Cambridge University Press:  07 July 2009

B. Chandrasekaran
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Extract

I thank the commentators for their time, and generally positive remarks on the promise of the task-specific approach, in particular the generic task (GT) proposal.

Johnson and Zualkernan would like a methodology for mapping domain knowledge onto one or more generic tasks so as to solve problems efficiently. This stage of problem and domain analysis in which the kind of reasoning that goes on needs to be analysed in a vocabulary of generic tasks is very important, and in our laboratory we identify this as the epistemic analysis stage. For specific classes of problems we have developed guidelines on how to perform this mapping. For example, Bylander and Smith (Bylander and Smith, 1985) describe a set of criteria and guidelines for mapping medical knowledge into CSRL-like structures for diagnostic reasoning. Similarly Brown (1984) describes criteria for mapping design knowledge into DSPL-like structures.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 3 , Issue 3 , September 1988 , pp. 217 - 219
Copyright
Copyright © Cambridge University Press 1988

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References

Brown, D C, 1984. Expert Systems for Design Problem-Solving using Design Refinement with Plan Selection and Redesign, PhD thesis, The Ohio State University, August.Google Scholar
Bylander, Tom and Smith, Jr, Jack, W, 1985. Mapping Medical Knowledge Into Conceptual Structures Ohio State University, Laboratory for AI Research, Technical Report.Google Scholar
Sembugamoorthy, V and Chandrasekaran, B, 1986. “Functional representation of devices and compilation of diagnostic problem solving systems” In: Experience, Memory and Reasoning, Kolodner, J. and Riesbeck, C. (Eds.), Lawrence Erlbaum Associates, pp. 47–73.Google Scholar
Goel, A and Chandrasekaran, B, 1988. “Integrating model-based reasoning and case-based reasoning for design problem solving” Ohio State University Laboratory for AI Research Technical Report. Also appears in Proc. AAAI Workshop on AI in Design, American Association for Artificial Intelligence, August 1988.Google Scholar
Sticklen, Jon, 1987. MDX2: An Integrated Medical Diagnostic System June. PhD Dissertation, Department of Computer & Information Science, The Ohio State University, Columbus, OH, USA.Google Scholar
Laird, J E, Newell, A and Rosenbloom, P S, 1987. “SOAR: An architecture for general intelligence” Artificial Intelligence 33, pp. 1–64.CrossRefGoogle Scholar