Abstract
Like humans, artificial neural networks can learn from examples. In supervised learning, an example consists of a “question” and its “answer.” The answer is provided by a “teacher” and used by the “student” to update her2 internal representation, i.e. the values of her neural weights. Using techniques from statistical mechanics, many properties arising from such a simple scheme have been investigated. The one-layered perceptron is a popular platform for these studies: it is complicated enough to arrive at interesting results, yet simple enough to be described analytically. Excellent reviews of the main achievements can be found in Seung et al. (1992), and Watkin et al. (1993).
In this paper, we will sometimes use rather colloquial language, hoping that this helps to elucidate some of the concepts. We sincerely apologize to any readers as males. This is definitely not an example of traditional role modeling, for in the end we will see how a smart female student outperforms her male teacher.
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Heskes, T. (2000). The Use of Being Stubborn and Introspective. In: Cruse, H., Dean, J., Ritter, H. (eds) Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic, Volume 1, Volume 2 Prerational Intelligence: Interdisciplinary Perspectives on the Behavior of Natural and Artificial Systems, Volume 3. Studies in Cognitive Systems, vol 26. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0870-9_75
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DOI: https://doi.org/10.1007/978-94-010-0870-9_75
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