Abstract
This paper presents a cognitive model for the three different types of human learning. To date, learning by being told [4], learning from examples [7], and learning by exploration have mostly been investigated in isolation as different machine learning procedures. We will first present the general assumptions of the proposed model and a description of the different learning methods. The model is then applied to describe what can be learned by the various learning methods and their combinations. Although the proposed model is general, we restrict this presentation to the learning of simple LISP functions.
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References
Hall, R. J. (1988). Learning by failing to explain: Using partial explanations to learn in incomplete or intractable domains. Machine Learning, 3, 1988.
Lewis, C. (1988). Why and how to learn why: analysis-based generalization of procedures. Cognitive Science, 12, 211–256.
Mitchell, T. M., Keller, R., & Kedar-Cabelli, S. (1986). Explanation-based generalization: A unifying view. Machine Learning, 1, –80.
Mostow, D. J. (1983). Machine transformation of advice into a heuristic search procedure. In R. Michalski, J. G. Carbonall, & T. M. Mitchell (Eds.), Machine Learning. Palo Alto, CA: Tioga.
Schmalhofer, F. (1986). The construction of programming knowledge from system explorations and explanatory text: a cognitive model. In C. R. Rollinger & W. Horn (Eds.), GWAI-86 and 2nd Austrian Artificial Intelligence Conference. Heidelberg: Springer, 152–163.
Schmalhofer, F., Khn, O. & Messamer, P. (1989). Receptive and exploratory learning in Intelligent Tutoring Systems. In: Alexander J. (Ed). Proceedings of the Rocky Mountain Conference on Artificial Intelligence, Denver.
Winston, P. H. (1975). Learning structural descriptions from examples. In P. H. Winston (Ed.), The psychology of computer vision. New York: McGraw-Hill.
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© 1989 Springer-Verlag Berlin Heidelberg
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Kühn, O., Schmalhofer, F. (1989). An Integrative Model of Learning by Being Told, from Examples and by Exploration. In: Metzing, D. (eds) GWAI-89 13th German Workshop on Artificial Intelligence. Informatik-Fachberichte, vol 216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-75100-4_49
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DOI: https://doi.org/10.1007/978-3-642-75100-4_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-51743-6
Online ISBN: 978-3-642-75100-4
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