Fact-Free Learning, Second Version
32 Pages Posted: 5 Jan 2005
Date Written: December 2004
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.
Note: A previous version of this abstract can be found at: http://ssrn.com/abstract=460203
Keywords: Learning, Behavioral Economics
JEL Classification: D11
Suggested Citation: Suggested Citation
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