Abstract
When I agreed to write this chapter, I thought I could simply expand a paper that I wrote for the Carnegie Symposium on Cognition, since the topic of that symposium was also learning. The difficulty with plagiarizing that paper is that it was really about psychology, whereas this book is concerned with machine learning. Now although we all believe machines can simulate human thought—unless we’re vitalists, and there aren’t any of those around any more—still, I didn’t think that was what was intended by the title of the book. I didn’t think it was appropriate to write about psychology.
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© 1983 Springer-Verlag Berlin Heidelberg
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Simon, H.A. (1983). Why Should Machines Learn?. In: Michalski, R.S., Carbonell, J.G., Mitchell, T.M. (eds) Machine Learning. Symbolic Computation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-12405-5_2
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DOI: https://doi.org/10.1007/978-3-662-12405-5_2
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