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Learning to Respond: The Use of Heuristics in Dynamic Games

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  • Mikhael Shor

    (Vanderbilt University)

Abstract

While many learning models have been proposed in the game theoretic literature to track individuals’ behavior, surprisingly little research has focused on how well these models describe human adaptation in changing dynamic environments. Analysis of human behavior demonstrates that people are often remarkably responsive to changes in their environment, on time scales ranging from millennia (evolution) to milliseconds (reflex). The goal of this paper is to evaluate several prominent learning models in light of a laboratory experiment on responsiveness in a lowinformation dynamic game subject to changes in its underlying structure. While history-dependent reinforcement learning models track convergence of play well in repeated games, it is shown that they are ill suited to these environments, in which sastisficing models accurately predict behavior. A further objective is to determine which heuristics, or “rules of thumb,” when incorporated into learning models, are responsible for accurately capturing responsiveness. Reference points and a particular type of experimentation are found to be important in both describing and predicting play.

Suggested Citation

  • Mikhael Shor, 2003. "Learning to Respond: The Use of Heuristics in Dynamic Games," Game Theory and Information 0301001, EconWPA.
  • Handle: RePEc:wpa:wuwpga:0301001
    Note: Type of Document - Acrobat PDF; prepared on IBM PC; to print on HP; pages: 34 ; figures: included. 35 pages, Acrobat PDF, figures included
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    File URL: http://econwpa.repec.org/eps/game/papers/0301/0301001.pdf
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    References listed on IDEAS

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    1. Karandikar, Rajeeva & Mookherjee, Dilip & Ray, Debraj & Vega-Redondo, Fernando, 1998. "Evolving Aspirations and Cooperation," Journal of Economic Theory, Elsevier, vol. 80(2), pages 292-331, June.
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    6. Selten, Reinhard, 1991. "Evolution, learning, and economic behavior," Games and Economic Behavior, Elsevier, vol. 3(1), pages 3-24, February.
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    9. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, Oxford University Press, vol. 69(1), pages 99-118.
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    Cited by:

    1. Nicolosi, Gina & Peng, Liang & Zhu, Ning, 2009. "Do individual investors learn from their trading experience?," Journal of Financial Markets, Elsevier, vol. 12(2), pages 317-336, May.
    2. Napel, Stefan, 2003. "Aspiration adaptation in the ultimatum minigame," Games and Economic Behavior, Elsevier, vol. 43(1), pages 86-106, April.
    3. D'Orlando, Fabio & Sanfilippo, Eleonora, 2010. "Behavioral foundations for the Keynesian consumption function," Journal of Economic Psychology, Elsevier, vol. 31(6), pages 1035-1046, December.

    More about this item

    Keywords

    learning; limited information; dynamic games;

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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