Compressed Environments: Unbounded Optimizers Should Sometimes Ignore Information

Minds and Machines, Vol. 20, No. 2, pp. 259-275, 2010

18 Pages Posted: 15 Oct 2010

See all articles by Nathan Berg

Nathan Berg

University of Otago, Department of Economics

Ulrich Hoffrage

University of Lausanne

Date Written: 2010

Abstract

Given free information and unlimited processing power, should decision algorithms use as much information as possible? A formal model of the decision making environment is developed to address this question and provide conditions under which informationally frugal algorithms, without any information or processing costs whatsoever, are optimal. One cause of compression that allows optimal algorithms to rationally ignore information is inverse movement of payoffs and probabilities (e.g., high payoffs occur with low probably and low payoffs occur with high probability). If inversely related payoffs and probabilities cancel out, then predictors that correlate with payoffs and consequently condition the probabilities associated with different payoffs will drop out of the expected-payoff objective function, severing the link between information and optimal action rules. Stochastic payoff processes in which rational ignoring occurs are referred to as compressed environments, because optimal action depends on a reduced-dimension subset of the environmental parameters. This paper considers benefits and limitations of economic models versus other methods for studying links between environmental structure and the real-world success of simple decision procedures. Different methods converge on the normative proposition of ecological rationality, as opposed to axiomatic rationality based on informational efficiency and internal consistency axioms, as a superior framework for comparing the effectiveness of decision strategies and prescribing decision algorithms in application.

Keywords: Ecological rationality, Bounded rationality, Frugality, Simplicity

JEL Classification: D03

Suggested Citation

Berg, Nathan and Hoffrage, Ulrich, Compressed Environments: Unbounded Optimizers Should Sometimes Ignore Information (2010). Minds and Machines, Vol. 20, No. 2, pp. 259-275, 2010, Available at SSRN: https://ssrn.com/abstract=1691964

Nathan Berg (Contact Author)

University of Otago, Department of Economics ( email )

P.O. Box 56
Dunedin, Otago 9016
New Zealand

Ulrich Hoffrage

University of Lausanne ( email )

Quartier Chambronne
Lausanne, Vaud CH-1015
Switzerland

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
17
Abstract Views
919
PlumX Metrics