The potential of machine learning techniques for expert systems

Yoram Reich, Steven J. Fenves

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


Expert systems employing current methodologies suffer from two major problems: they are brittle and their development is time-consuming and tedious. Learning, the key to intelligent human behavior and expertise, has the potential of alleviating these difficulties. The paper reviews a number of machine learning techniques and provides a framework for their classification. The description of each technique is followed by an example taken from the domain of structural design. The applicability of machine learning techniques to expert systems is discussed, including some prototype applications and their shortcomings. Three promising research directions are outlined as a partial solution for the shortcomings.

Original languageEnglish
Pages (from-to)175-193
Number of pages19
JournalArtificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Issue number3
StatePublished - Aug 1989
Externally publishedYes


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