Fact-Free Learning

Enriqueta Aragones, Itzhak Gilboa, Andrew Postlewaite and David Schmeidler

Chapter 8 in Case-Based Predictions:An Axiomatic Approach to Prediction, Classification and Statistical Learning, 2012, pp 185-210 from World Scientific Publishing Co. Pte. Ltd.

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.

Keywords: Case-Based Reasoning; Case-Based Decision Theory; Statistics; Decision Under Uncertainty (search for similar items in EconPapers)
Date: 2012
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Related works:
Journal Article: Fact-Free Learning (2005)
Working Paper: Fact-Free Learning (2005)
Working Paper: Fact-Free Learning (2004)
Working Paper: Fact-Free Learning (2004)
Working Paper: Fact-Free Learning (2003)
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