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Clever agents in adaptive learning

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  • Matros, Alexander

Abstract

Saez-Marti and Weibull [4] investigate the consequences of letting some agents play a myopic best reply to the myopic best reply in Young's [8] bargaining model. This is how they introduce ''cleverness'' of players. We analyze such clever agents in general finite two-player games. We show that Young's [9] prediction is robust: adaptive learning with clever agents does select the same minimal curb set as in the absence of clever agents, if their population share is less than one. However, the long-run strategies distribution in such a curb set may vary with the share of clever agents.
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Suggested Citation

  • Matros, Alexander, 2003. "Clever agents in adaptive learning," Journal of Economic Theory, Elsevier, vol. 111(1), pages 110-124, July.
    • Handle: RePEc:eee:jetheo:v:111:y:2003:i:1:p:110-124
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    1. 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.
    2. Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
    3. Basu, Kaushik & Weibull, Jorgen W., 1991. "Strategy subsets closed under rational behavior," Economics Letters, Elsevier, vol. 36(2), pages 141-146, June.
    4. Hurkens Sjaak, 1995. "Learning by Forgetful Players," Games and Economic Behavior, Elsevier, vol. 11(2), pages 304-329, November.
    5. Young H. P., 1993. "An Evolutionary Model of Bargaining," Journal of Economic Theory, Elsevier, vol. 59(1), pages 145-168, February.
    6. P. Young, 1999. "The Evolution of Conventions," Levine's Working Paper Archive 485, David K. Levine.
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    Cited by:

    1. Nax, Heinrich Harald & Newton, Jonathan, 2022. "Deep and shallow thinking in the long run," Theoretical Economics, Econometric Society, vol. 17(4), November.
    2. Andriy Zapechelnyuk, 2009. "Limit Behavior of No-regret Dynamics," Discussion Papers 21, Kyiv School of Economics.
    3. Josephson, Jens, 2009. "Stochastic adaptation in finite games played by heterogeneous populations," Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1543-1554, August.
    4. Takako Fujiwara-Greve & Carsten Krabbe Nielsen, 2021. "Algorithms may not learn to play a unique Nash equilibrium," Journal of Computational Social Science, Springer, vol. 4(2), pages 839-850, November.
    5. 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.
    6. Alexander Matros, 2006. "Altruistic Versus Rational Behavior in a Public Good Game," Working Paper 309, Department of Economics, University of Pittsburgh, revised Sep 2008.
    7. 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.
    8. Matros, Alexander, 2012. "Altruistic versus egoistic behavior in a Public Good game," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 642-656.
    9. Khan, Abhimanyu, 2021. "Evolutionary stability of behavioural rules in bargaining," Journal of Economic Behavior & Organization, Elsevier, vol. 187(C), pages 399-414.

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    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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