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Knowledge acquisition on neural networks

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Uncertainty and Intelligent Systems (IPMU 1988)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 313))

Abstract

A knowledge acquisition system is implemented on the IBM PAN (Parallel Associative Networks) system. This is an iterative process that reduces the uncertainty of a body of knowledge and information at each time step and produces a convergent result which provides certainty to this body. This scheme of uncertainty management is similar to human thinking and decision making processes. The characteristics of noncrisp (or fuzzy) and multi-valued reasoning and gradual improvement of understanding are captured by a mathematically rigorous model which is implemented conveniently on a neural network processor.

This research has been partially supported by the National Science Foundation.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of North Carolina, 28223, Charlotte, North Carolina

    Su-shing Chen

Authors
  1. Su-shing Chen
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Editor information

B. Bouchon L. Saitta R. R. Yager

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© 1988 Springer-Verlag Berlin Heidelberg

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Chen, Ss. (1988). Knowledge acquisition on neural networks. In: Bouchon, B., Saitta, L., Yager, R.R. (eds) Uncertainty and Intelligent Systems. IPMU 1988. Lecture Notes in Computer Science, vol 313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-19402-9_83

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  • DOI: https://doi.org/10.1007/3-540-19402-9_83

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19402-6

  • Online ISBN: 978-3-540-39255-2

  • eBook Packages: Springer Book Archive

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