Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12376
Title: Learning design knowledge as generalization
Authors: Li, H 
Wu, X
Issue Date: 1998
Source: Cybernetics and systems, 1998, v. 29, no. 2, p. 181-207 How to cite?
Journal: Cybernetics and Systems 
Abstract: Generalizing design knowledge is a process of extracting knowledge from design-provided data. Although it is one of the most common ways of "learning" design knowledge, generalization has a fundamental weakness: except for special occasions, the results of generalization can never be validated. Inquiries into generalization have therefore dealt with questions of what are the best criteria for guiding the generalization. This paper argues that generalizing design knowledge involves three essential tasks; knowledge representation, a description language for design examples, and generalization operators. An application of generalizing empirical networks from design examples is described to illustrate these three tasks in the development of a generalization system.
URI: http://hdl.handle.net/10397/12376
ISSN: 0196-9722
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