IDEAS home Printed from https://ideas.repec.org/p/msh/ebswps/2001-8.html
   My bibliography  Save this paper

Strategy Similarity and Coordination

Author

Listed:
  • Vahid, F.
  • Sarin, R.

Abstract

This paper introduces similarity among strategies in the payoff assessment model of choice (Sarin and Vahid (1999, GEB)). The assessments of strategies that are more similar to the chosen strategy are updated more similarly to the chosen strategy. We use this model to explain a recent experiment.

Suggested Citation

  • Vahid, F. & Sarin, R., 2001. "Strategy Similarity and Coordination," Monash Econometrics and Business Statistics Working Papers 8/01, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2001-8
    as

    Download full text from publisher

    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2001/wp8-01.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Beggs Alan, 2009. "Learning in Bayesian Games with Binary Actions," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 9(1), pages 1-30, September.
    2. Ralph-C Bayer & Elke Renner & Rupert Sausgruber, 2009. "Confusion and Reinforcement Learning in Experimental Public Goods Games," NRN working papers 2009-22, The Austrian Center for Labor Economics and the Analysis of the Welfare State, Johannes Kepler University Linz, Austria.
    3. Teck H. Ho & Xin Wang & Colin F. Camerer, 2008. "Individual Differences in EWA Learning with Partial Payoff Information," Economic Journal, Royal Economic Society, vol. 118(525), pages 37-59, January.
    4. Ralph-C. Bayer & Elke Renner & Rupert Sausgruber, 2013. "Confusion and learning in the voluntary contributions game," Experimental Economics, Springer;Economic Science Association, vol. 16(4), pages 478-496, December.
    5. Oyarzun, Carlos & Ruf, Johannes, 2014. "Convergence in models with bounded expected relative hazard rates," Journal of Economic Theory, Elsevier, vol. 154(C), pages 229-244.
    6. Dürsch, Peter & Kolb, Albert & Oechssler, Jörg & Schipper, Burkhard C., 2005. "Rage Against the Machines: How Subjects Learn to Play Against Computers," Bonn Econ Discussion Papers 31/2005, University of Bonn, Bonn Graduate School of Economics (BGSE).
    7. Castañeda, Gonzalo & Chávez-Juárez, Florian & Guerrero, Omar A., 2018. "How do governments determine policy priorities? Studying development strategies through spillover networks," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 335-361.
    8. Brit Grosskopf & Rajiv Sarin & Elizabeth Watson, 2015. "An experiment on case-based decision making," Theory and Decision, Springer, vol. 79(4), pages 639-666, December.
    9. Hu Sun & Yun Wang, 2019. "Do On-lookers See Most of the Game? Evaluating Job-seekers' Competitiveness of Oneself versus of Others in a Labor Market Experiment," Working Papers 2019-07-11, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    10. Wu, Hang & Bayer, Ralph-C, 2015. "Learning from inferred foregone payoffs," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 445-458.
    11. Peter Duersch & Albert Kolb & Jörg Oechssler & Burkhard Schipper, 2010. "Rage against the machines: how subjects play against learning algorithms," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 43(3), pages 407-430, June.
    12. Mohlin, Erik & Östling, Robert & Wang, Joseph Tao-yi, 2020. "Learning by similarity-weighted imitation in winner-takes-all games," Games and Economic Behavior, Elsevier, vol. 120(C), pages 225-245.
    13. Dürsch, Peter & Kolb, Albert & Oechssler, Jörg & Schipper, Burkhard, 2005. "Rage against the machines : how subjects learn to play against computers," Papers 05-36, Sonderforschungsbreich 504.

    More about this item

    Keywords

    Econometric analysis of experimental data; Adaptive learning; Similarity; Coordination games; Payoff assessments without probabilities;
    All these keywords.

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

    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:msh:ebswps:2001-8. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Professor Xibin Zhang (email available below). General contact details of provider: https://edirc.repec.org/data/dxmonau.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.