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International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems

IPMU 1988: Uncertainty and Intelligent Systems pp 171–178Cite as

Controlling inductive search in rigel learning system

  • Knowledge Acquisition And Machine Learning
  • Conference paper
  • First Online:

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

Abstract

Concept induction from examples has already proved to work on significant case studies and will be a fundamental tool in next generation expert systems. For this reason it is important to improve induction techniques, particularly to face real world problems. A tipical problem of real application is the width of the state spaces to be searched. This problem has been faced in the design of the inductive learning system RIGEL, which explicitly represents and uses task dependent (but domain independent) control knowledge to strongly focus the inductive search. RIGEL has been implemented in Common Lisp on TI Explorer, Symbolics and Sun and tested on several case studies taken from literature. At present it is beeing applied to a real problem, taken from the image recognition field.

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References

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Author information

Authors and Affiliations

  1. CSELT, Computer Science Division, Artificial Intelligence Department, Via Reiss Romoli 274, 10148, Torino

    R. Gemello & F. Mana

Authors
  1. R. Gemello
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  2. F. Mana
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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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Gemello, R., Mana, F. (1988). Controlling inductive search in rigel learning system. 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_70

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  • DOI: https://doi.org/10.1007/3-540-19402-9_70

  • 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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