Executing Complex Cognitive Tasks: Prizes vs. Markets

40 Pages Posted: 5 Mar 2007

See all articles by Peter Bossaerts

Peter Bossaerts

University of Melbourne - Department of Finance; University of Cambridge

Debrah Meloso

Toulouse Business School - TBS Education

Jernej Copic

Yale University - Cowles Foundation

Date Written: November 22, 2006

Abstract

Execution of complex cognitive tasks is often analyzed as an exercise of information acquisition and belief updating. We challenge this view in the context of a non-incremental task, namely, the knapsack problem. First, we provide a theoretical argument why Bayesian updating makes little sense in this context. Second, we provide experimental evidence against the Bayesian approach by comparing the quality of problem solving under two treatments: prizes; markets. We find that Bayesian theory cannot make sense of the data: both systems work equally well, while trading is abundant in the market setup and prices are informative but noisy. The experimental data provide suggestions for a new theory of discovery of solutions in non-incremental tasks.

Keywords: Intellectual Discovery, Markets, Computation, non-Bayesian Learning

JEL Classification: C92, D23, D52, D83

Suggested Citation

Bossaerts, Peter L. and Meloso, Debrah C and Copic, Jernej, Executing Complex Cognitive Tasks: Prizes vs. Markets (November 22, 2006). Available at SSRN: https://ssrn.com/abstract=968151 or http://dx.doi.org/10.2139/ssrn.968151

Peter L. Bossaerts

University of Melbourne - Department of Finance ( email )

Faculty of Economics and Commerce
Department of Finance
Carlton, Victoria 3010
Australia

HOME PAGE: http://bmmlab.org

University of Cambridge ( email )

Trinity Ln
Cambridge, CB2 1TN
United Kingdom

Debrah C Meloso

Toulouse Business School - TBS Education ( email )

Toulouse
France

Jernej Copic (Contact Author)

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States
302 4326258 (Phone)

HOME PAGE: http://www.hss.caltech.edu/~jernej

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