Fact-Free Learning

35 Pages Posted: 24 Nov 2004  

Enriqueta Aragones

Spanish Council for Scientific Research (CSIC) - Insitute for Economic Analysis

Itzhak Gilboa

Tel Aviv University - Eitan Berglas School of Economics; HEC Paris - Economics & Decision Sciences

Andrew Postlewaite

University of Pennsylvania - Department of Economics

David Schmeidler

Tel Aviv University

Date Written: October 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 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.

Notes: An updated version of this abstract can be found at: http://ssrn.com/abstract=643545

Keywords: Computational complexity, Linear regression, Rule-based reasoning

JEL Classification: C8, D8

Suggested Citation

Aragones, Enriqueta and Gilboa, Itzhak and Postlewaite, Andrew and Schmeidler, David, Fact-Free Learning (October 2004). PIER Working Paper No. 03-023; Cowles Foundation Discussion Paper No. 1491. Available at SSRN: https://ssrn.com/abstract=460203

Enriqueta Aragon├ęs

Spanish Council for Scientific Research (CSIC) - Insitute for Economic Analysis ( email )

08193 Bellaterra
Spain
34-93-580-6612 (Phone)
34-93-580-1452 (Fax)

Itzhak Gilboa (Contact Author)

Tel Aviv University - Eitan Berglas School of Economics ( email )

P.O. Box 39040
Ramat Aviv, Tel Aviv, 69978
Israel
972-3-640-6423 (Phone)
972-3-640-9908 (Fax)

HEC Paris - Economics & Decision Sciences

Paris
France

Andrew Postlewaite

University of Pennsylvania - Department of Economics ( email )

160 McNeil Building
3718 Locust Walk
Philadelphia, PA 19104
United States
215-898-7350 (Phone)
215-573-2057 (Fax)

HOME PAGE: http://www.econ.upenn.edu/~apostlew

David Schmeidler

Tel Aviv University ( email )

P.O. Box 39040
Ramat Aviv, Tel Aviv, 69978
Israel
+972-3-640-9643 (Phone)
+972-3-640-9357 (Fax)

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