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Fact-free learning

delete2005-11-01
delete60
delete
OA
AI
A
Aragones, E
G
Gilboa, I
A
Andrew Postlewaite
D
David Schmeidler
DOI：10.1257/000282805775014308delete
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Abstract

Abstract

En 中文
People may be surprised to notice 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 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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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

American Economic Review cover
American Economic Review
IF:
11.6
Papers:
5.0K
Citations:
7.5W

Organization

No organization information available