Models of Learning Systems.
STANFORD UNIV CALIF DEPT OF COMPUTER SCIENCE
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The terms adaptation, learning, concept-formation, induction, self-organization, and self-repair have all been used in the context of learning system LS research. In this article, three distinct approaches to machine learning and adaptation are considered i the adaptive control approach, ii the pattern recognition approach, and iii the artificial intelligence approach. Progress in each of these areas is summarized in the first part of the article. In the next part a general model for learning systems is presented that allows characterization and comparison of individual algorithms and programs in all of these areas. The model details the functional components felt to be essential for any learning system, independent of the techniques used for its construction, and the specific environment in which it operates. Specific examples of learning systems are described in terms of the model. Author
- Human Factors Engineering and Man Machine Systems