IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/20060034.html
   My bibliography  Save this paper

Learning in a Local Interaction Hawk-Dove Game

Author

Listed:
  • Jurjen Kamphorst

    (Faculty of Law, Leiden University)

  • Gerard van der Laan

    (Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam)

Abstract

We study how players in a local interaction hawk dove game will learn, if they can either imitate the most succesful player in the neighborhood or play a best reply versus the opponent's previous action. From simulations it appears that each learning strategy will be used, because each performs better when it is less popular. Despite that, clustering may occur if players choose their learning strategy on the basis of largely similar information. Finally, on average players will play Hawk with a probability larger than in the mixed Nash equilibrium of the stage game.

Suggested Citation

  • Jurjen Kamphorst & Gerard van der Laan, 2006. "Learning in a Local Interaction Hawk-Dove Game," Tinbergen Institute Discussion Papers 06-034/1, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20060034
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/06034.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    2. Alexander Tieman & Harold Houba & Gerard Laan, 2000. "On the level of cooperative behavior in a local-interaction model," Journal of Economics, Springer, vol. 71(1), pages 1-30, February.
    3. Droste, Edward & Hommes, Cars & Tuinstra, Jan, 2002. "Endogenous fluctuations under evolutionary pressure in Cournot competition," Games and Economic Behavior, Elsevier, vol. 40(2), pages 232-269, August.
    4. Josephson, Jens, 2008. "A numerical analysis of the evolutionary stability of learning rules," Journal of Economic Dynamics and Control, Elsevier, vol. 32(5), pages 1569-1599, May.
    5. Possajennikov, A., 2000. "Learning and evolution in games and oligopoly models," Other publications TiSEM be1a3e81-e186-46b5-9101-3, Tilburg University, School of Economics and Management.
    6. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, December.
    7. Joëlle Noailly & Cees Withagen & Jeroen Bergh, 2007. "Spatial Evolution of Social Norms in a Common-Pool Resource Game," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(1), pages 113-141, January.
    8. Eshel, Ilan & Samuelson, Larry & Shaked, Avner, 1998. "Altruists, Egoists, and Hooligans in a Local Interaction Model," American Economic Review, American Economic Association, vol. 88(1), pages 157-179, March.
    9. Anderlini, Luca & Ianni, Antonella, 1996. "Path Dependence and Learning from Neighbors," Games and Economic Behavior, Elsevier, vol. 13(2), pages 141-177, April.
    10. Vega-Redondo, Fernando (ed.), 1996. "Evolution, Games, and Economic Behaviour," OUP Catalogue, Oxford University Press, number 9780198774723.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Goyal, Sanjeev, 2003. "Learning in Networks: a survey," Economics Discussion Papers 9983, University of Essex, Department of Economics.
    2. Alós-Ferrer, Carlos & Weidenholzer, Simon, 2008. "Contagion and efficiency," Journal of Economic Theory, Elsevier, vol. 143(1), pages 251-274, November.
    3. Simon Weidenholzer, 2010. "Coordination Games and Local Interactions: A Survey of the Game Theoretic Literature," Games, MDPI, vol. 1(4), pages 1-35, November.
    4. Waters, George A., 2009. "Chaos in the cobweb model with a new learning dynamic," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1201-1216, June.
    5. Ball, Richard, 2017. "Violations of monotonicity in evolutionary models with sample-based beliefs," Economics Letters, Elsevier, vol. 152(C), pages 100-104.
    6. Mohlin, Erik, 2012. "Evolution of theories of mind," Games and Economic Behavior, Elsevier, vol. 75(1), pages 299-318.
    7. Bayer, Péter & Herings, P. Jean-Jacques & Peeters, Ronald, 2021. "Farsighted manipulation and exploitation in networks," Journal of Economic Theory, Elsevier, vol. 196(C).
    8. Alos-Ferrer, Carlos & Weidenholzer, Simon, 2007. "Partial bandwagon effects and local interactions," Games and Economic Behavior, Elsevier, vol. 61(2), pages 179-197, November.
    9. Ludo Waltman & Nees Eck & Rommert Dekker & Uzay Kaymak, 2013. "An Evolutionary Model of Price Competition Among Spatially Distributed Firms," Computational Economics, Springer;Society for Computational Economics, vol. 42(4), pages 373-391, December.
    10. Pietro Dindo & Jan Tuinstra, 2011. "A Class of Evolutionary Models for Participation Games with Negative Feedback," Computational Economics, Springer;Society for Computational Economics, vol. 37(3), pages 267-300, March.
    11. Juana Santamaria-Garcia, 2009. "Bargaining Power In The Nash Demand Game An Evolutionary Approach," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 87-97.
    12. Jiang, Ge & Weidenholzer, Simon, 2016. "Local Interactions under Switching Costs," Economics Discussion Papers 17770, University of Essex, Department of Economics.
    13. Anke Gerbery & Thorsten Hensz & Bodo Vogtx, 2010. "Rational Investor Sentimentina Repeated Stochastic Game with Imperfect Monitoring," Post-Print hal-00911824, HAL.
    14. Ge Jiang & Simon Weidenholzer, 2017. "Local interactions under switching costs," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 64(3), pages 571-588, October.
    15. Anufriev, Mikhail & Kopányi, Dávid & Tuinstra, Jan, 2013. "Learning cycles in Bertrand competition with differentiated commodities and competing learning rules," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2562-2581.
    16. Jacques Durieu & Philippe Solal, 2012. "Models of Adaptive Learning in Game Theory," Chapters, in: Richard Arena & Agnès Festré & Nathalie Lazaric (ed.), Handbook of Knowledge and Economics, chapter 11, Edward Elgar Publishing.
    17. Schipper, Burkhard C, 2011. "Strategic control of myopic best reply in repeated games," MPRA Paper 30219, University Library of Munich, Germany.
    18. Ennio Bilancini & Leonardo Boncinelli & Alessandro Tampieri, 2021. "Strategy Assortativity and the Evolution of Parochialism," DEM Discussion Paper Series 21-20, Department of Economics at the University of Luxembourg.
    19. Ho, Teck H. & Camerer, Colin F. & Chong, Juin-Kuan, 2007. "Self-tuning experience weighted attraction learning in games," Journal of Economic Theory, Elsevier, vol. 133(1), pages 177-198, March.
    20. John P. Conley & Myrna Wooders, 2005. "Memetics & Voting: How Nature May Make us Public Spirited," Vanderbilt University Department of Economics Working Papers 0514, Vanderbilt University Department of Economics.

    More about this item

    Keywords

    Learning; Local Interaction; Hawk-Dove game;
    All these keywords.

    JEL classification:

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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tin:wpaper:20060034. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.