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Fact-Free Learning

In: Case-Based Predictions An Axiomatic Approach to Prediction, Classification and Statistical Learning

Author

Listed:
  • Enriqueta Aragones
  • Itzhak Gilboa
  • Andrew Postlewaite
  • David Schmeidler

Abstract

People may be surprised by noticing certain regularities that hold in existing knowledge they have had for some time. That is, they may learn without getting new factual information. We argue that this can be partly explained by computational complexity. We show that, given a knowledge base, finding a small set of variables that obtain a certain value of R2 is computationally hard, in the sense that this term is used in computer science.We discuss some of the implications of this result and of fact-free learning in general.

Suggested Citation

  • Enriqueta Aragones & Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2012. "Fact-Free Learning," World Scientific Book Chapters, in: Case-Based Predictions An Axiomatic Approach to Prediction, Classification and Statistical Learning, chapter 8, pages 185-210, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789814366182_0008
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    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory

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