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A model for learning by source control

  • Knowledge Acquisition And Machine Learning
  • Conference paper
  • First Online:
Book cover Uncertainty and Intelligent Systems (IPMU 1988)

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

Abstract

The information we receive is often changing, inconsistent and incomplete, thus bound to generate contradictions. Clearly we must recover reasonably from inconsistencies if to make sense of the world. We introduce a model to cope with this situation. This paper continues the work presented in (6,7). We propose that an adaptive reasoning system should use a model of its sources, recognise patterns in their behaviour and adjust that model on the basis of evidence and general principles. The relation with TMS is then discussed.

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Author information

Authors and Affiliations

  1. School of Engineering and Applied Science, University of Durham, England

    Roberto Garigliano & Albert Bokma

  2. Dept. of Computer Science, University College, London

    Derek Long

Authors
  1. Roberto Garigliano
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  2. Albert Bokma
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  3. Derek Long
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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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Garigliano, R., Bokma, A., Long, D. (1988). A model for learning by source control. 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_69

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  • DOI: https://doi.org/10.1007/3-540-19402-9_69

  • Published:

  • 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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