The Challenge of Flexible Intelligence for Models of Human Behavior

Technical Report of Association for the Advancement of Artificial Intelligence, Spring Symposium, 2012

Marshall School of Business Working Paper No. FBE 03-12

8 Pages Posted: 19 Jan 2012 Last revised: 9 May 2012

See all articles by Mathew D. McCubbins

Mathew D. McCubbins

Department of Political Science and Law School, Duke University (deceased)

Mark B. Turner

Case Western Reserve University - Department of Cognitive Science

Nicholas Weller

University of California, Riverside (UCR)

Date Written: January 18, 2012

Abstract

Game theoretic predictions about equilibrium behavior depend upon assumptions of inflexibility of belief, of accord between belief and choice, and of choice across situations that share a game-theoretic structure. However, researchers rarely possess any knowledge of the actual beliefs of subjects, and rarely compare how a subject behaves in settings that share game-theoretic structure but that differ in other respects. Our within-subject experiments utilize a belief elicitation mechanism, roughly similar to a prediction market, in a laboratory setting to identify subjects’ beliefs about other subjects’ choices and beliefs. These experiments additionally allow us to compare choices in different settings that have similar game-theoretic structure. We find first, as have others, that subjects’ choices in the Trust and related games are significantly different from the strategies that derive from subgame perfect Nash equilibrium principles. We show that, for individual subjects, there is considerable flexibility of choice and belief across similar tasks and that the relationship between belief and choice is similarly flexible. To improve our ability to predict human behavior, we must take account of the flexible nature of human belief and choice.

Keywords: game theory, economics, human behavior, experiments

Suggested Citation

McCubbins, Mathew D. and Turner, Mark B. and Weller, Nicholas, The Challenge of Flexible Intelligence for Models of Human Behavior (January 18, 2012). Technical Report of Association for the Advancement of Artificial Intelligence, Spring Symposium, 2012, Marshall School of Business Working Paper No. FBE 03-12 , Available at SSRN: https://ssrn.com/abstract=1987668

Mathew D. McCubbins

Department of Political Science and Law School, Duke University (deceased)

Mark B. Turner

Case Western Reserve University - Department of Cognitive Science ( email )

10900 Euclid Avenue
Cleveland, OH 44106-7068
United States

HOME PAGE: http://markturner.org

Nicholas Weller (Contact Author)

University of California, Riverside (UCR) ( email )

900 University Avenue
Riverside, CA CA 92521
United States

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