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Cognitive hierarchies in adaptive play

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  • Abhimanyu Khan
  • Ronald Peeters

Abstract

Inspired by the behavior in repeated guessing game experiments, we study adaptive play by populations containing individuals that reason with different levels of cognition. Individuals play a higher order best response to samples from the empirical data on the history of play, where the order of best response is determined by their exogenously given level of cognition. As in Young’s model of adaptive play, (unperturbed) play still converges to a minimal curb set. Random perturbations of the best response dynamic identifies the stochastically stable states. In Young’s model of adaptive play with simple best-responses, the set of stochastically stable states are sensitive to the sample size that individuals from a population can draw. In generic games with higher order best-responders in both populations, the sample size is rendered irrelevant in determination of the stochastically stable set. Perhaps counter-intuitively, higher cognition may actually be bad for both the individual with higher cognition and his parent population. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Abhimanyu Khan & Ronald Peeters, 2014. "Cognitive hierarchies in adaptive play," International Journal of Game Theory, Springer;Game Theory Society, vol. 43(4), pages 903-924, November.
  • Handle: RePEc:spr:jogath:v:43:y:2014:i:4:p:903-924
    DOI: 10.1007/s00182-014-0410-5
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    1. Stahl Dale O. & Wilson Paul W., 1995. "On Players' Models of Other Players: Theory and Experimental Evidence," Games and Economic Behavior, Elsevier, vol. 10(1), pages 218-254, July.
    2. Ritzberger, Klaus & Weibull, Jorgen W, 1995. "Evolutionary Selection in Normal-Form Games," Econometrica, Econometric Society, vol. 63(6), pages 1371-1399, November.
    3. Saez-Marti, Maria & Weibull, Jorgen W., 1999. "Clever Agents in Young's Evolutionary Bargaining Model," Journal of Economic Theory, Elsevier, vol. 86(2), pages 268-279, June.
    4. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
    5. Basu, Kaushik & Weibull, Jorgen W., 1991. "Strategy subsets closed under rational behavior," Economics Letters, Elsevier, vol. 36(2), pages 141-146, June.
    6. Matros, Alexander, 2003. "Clever agents in adaptive learning," Journal of Economic Theory, Elsevier, vol. 111(1), pages 110-124, July.
    7. Binmore, Ken, 1988. "Modeling Rational Players: Part II," Economics and Philosophy, Cambridge University Press, vol. 4(1), pages 9-55, April.
    8. Nagel, Rosemarie, 1995. "Unraveling in Guessing Games: An Experimental Study," American Economic Review, American Economic Association, vol. 85(5), pages 1313-1326, December.
    9. Hurkens Sjaak, 1995. "Learning by Forgetful Players," Games and Economic Behavior, Elsevier, vol. 11(2), pages 304-329, November.
    10. Mohlin, Erik, 2012. "Evolution of theories of mind," Games and Economic Behavior, Elsevier, vol. 75(1), pages 299-318.
    11. Joseph Tao-yi Wang & Michael Spezio & Colin F. Camerer, 2010. "Pinocchio's Pupil: Using Eyetracking and Pupil Dilation to Understand Truth Telling and Deception in Sender-Receiver Games," American Economic Review, American Economic Association, vol. 100(3), pages 984-1007, June.
    12. Young H. P., 1993. "An Evolutionary Model of Bargaining," Journal of Economic Theory, Elsevier, vol. 59(1), pages 145-168, February.
    13. Binmore, Ken, 1987. "Modeling Rational Players: Part I," Economics and Philosophy, Cambridge University Press, vol. 3(2), pages 179-214, October.
    14. Vincent P. Crawford & Nagore Iriberri, 2007. "Fatal Attraction: Salience, Naivete, and Sophistication in Experimental Hide-and-Seek Games," Levine's Bibliography 321307000000000861, UCLA Department of Economics.
    15. Stahl Dale O., 1993. "Evolution of Smartn Players," Games and Economic Behavior, Elsevier, vol. 5(4), pages 604-617, October.
    16. Stahl, Dale II & Wilson, Paul W., 1994. "Experimental evidence on players' models of other players," Journal of Economic Behavior & Organization, Elsevier, vol. 25(3), pages 309-327, December.
    17. Colin F. Camerer & Teck-Hua Ho & Juin-Kuan Chong, 2004. "A Cognitive Hierarchy Model of Games," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(3), pages 861-898.
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    Cited by:

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    3. Khan, Abhimanyu, 2021. "Evolutionary stability of behavioural rules in bargaining," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 399-414.
    4. Abhimanyu Khan, 2021. "Evolution of conventions in games between behavioural rules," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 9(2), pages 209-224, October.

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    More about this item

    Keywords

    Evolution of behavior; Adaptive play; Cognitive hierarchies; Level- $$k$$ k reasoning; C73; D03;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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