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Fact-Free Learning

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 database, finding a small set of variables that obtain a certain value of R^2 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.
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https://hal-hec.archives-ouvertes.fr/hal-00481243
Contributor : Antoine Haldemann <>
Submitted on : Thursday, May 6, 2010 - 11:49:36 AM
Last modification on : Monday, October 29, 2012 - 1:06:12 PM

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Itzhak Gilboa, Enriqueta Aragones, Andrew Postlewaite, David Schmeidler. Fact-Free Learning. American Economic Review, American Economic Association, 2005, Vol.95, pp.1355-1368. ⟨10.1257/000282805775014308⟩. ⟨hal-00481243⟩

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