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Adaptive expert systems and analogical problem solving

  • Data And Software Engineering
  • Conference paper
  • First Online:
Advances in Computing and Information — ICCI '90 (ICCI 1990)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 468))

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Abstract

Conventional expert systems are "brittle" in the sense that they require substantial human intervention to compensate for even slight variations in descriptions, and break easily when they reach the edge of their knowledge. In response to this problem, this paper describes a prototype of a new generation of expert systems, called an adaptive expert system (AES), which is capable of adapting its knowledge dynamically and analogically. AES combines the focussed power of expert systems with the analogical problem solving abilities of case-based reasoning systems, and demonstrates much higher "IQs" than the expert systems currently available on the market.

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References

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Author information

Authors and Affiliations

  1. Department of Computer and Information Sciences, Towson State University, 21204, Towson, MD, U.S.A.

    H. Harry Zhou

Authors
  1. H. Harry Zhou
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Editor information

S. G. Akl F. Fiala W. W. Koczkodaj

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© 1991 Springer-Verlag Berlin Heidelberg

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Zhou, H.H. (1991). Adaptive expert systems and analogical problem solving. In: Akl, S.G., Fiala, F., Koczkodaj, W.W. (eds) Advances in Computing and Information — ICCI '90. ICCI 1990. Lecture Notes in Computer Science, vol 468. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-53504-7_89

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  • DOI: https://doi.org/10.1007/3-540-53504-7_89

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-53504-1

  • Online ISBN: 978-3-540-46677-2

  • eBook Packages: Springer Book Archive

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