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Why Should Machines Learn?

  • Herbert A. Simon
Part of the Symbolic Computation book series (SYMBOLIC)

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.

Keywords

Machine Learning Natural Language Internal Representation Human Learning Automatic Programming 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1983

Authors and Affiliations

  • Herbert A. Simon
    • 1
  1. 1.Carnegie-Mellon UniversityUSA

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