Models of Learning Systems

Models of Learning Systems

Auteur : Stanford University. Computer Science Department, Bruce G. Buchanan, T. M. Mitchell, R. G. Smith

Date de publication : 1979

Éditeur : Computer Science Department, Stanford University

Nombre de pages : 40

Résumé du livre

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).

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