Knowledge oriented learning

  • Authors:

  • Paul D. Scott;Robert C. Vogt

  • Affiliations:

  • Department of Computer and Communication Sciences, University of Michigan;Department of Computer and Communication Sciences, University of Michigan

  • Venue:
  • IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
  • Year:
  • 1983

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Abstract

Two alternative learning strategies are defined and discussed: Task-oriented learning in which a system tries to improve its performance at a specified task and knowledge-oriented learning in which a system builds an organised representation of experience. It is argued that the relationship between these two strategies is analagous to the relationship between technology and science. Hence it is concluded that the development of knowledge-oriented learning systems, which has been largely overlooked by the AI community, is a worth while research goal. We then proceed to describe how such a system may be constructed by building a machine which continually tries to reduce its own uncertainty regarding the outcome of its actions. An implementation which learns to perform a multiple concept learning task in the presence of noisy data is briefly described.