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Learning in Networks - An Experimental Study using Stationary Concepts

Author

Listed:
  • Siegried K. Berninghaus

    (Karlsruhe Institute of Technology (KIT), Institute for Economic Theory and Statistics)

  • Thomas Neumann

    () (Otto-von-Guericke-University Magdeburg, Faculty of Economics and Management, Empirical Economics)

  • Bodo Vogt

    (Otto-von-Guericke-University Magdeburg, Faculty of Economics and Management, Empirical Economics)

Abstract

Our study analyzes theories of learning for strategic interactions in networks. Participants played two of the 2 x 2 games used by Selten and Chmura (2008) and in the comment by Brunner, Camerer and Goeree (2009). Every participant played against four neighbors and could choose a different strategy against each of them. The games were played in two network structures: a attice and a circle. We compare our results with the predictions of different theories (Nash equilibrium, quantal response equilibrium, action-sampling equilibrium, payoff-sampling equilibrium, and impulse balance equilibrium) and the experimental results of Selten and Chmura (2008). One result is that the majority of players choose the same strategy against each neighbor. As another result we observe an order of predictive success for the stationary concepts that is different from the order shown by Selten and Chmura. This result supports our view that learning in networks is different from learning in random matching.

Suggested Citation

  • Siegried K. Berninghaus & Thomas Neumann & Bodo Vogt, 2011. "Learning in Networks - An Experimental Study using Stationary Concepts," Jena Economic Research Papers 2011-048, Friedrich-Schiller-University Jena.
  • Handle: RePEc:jrp:jrpwrp:2011-048
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    References listed on IDEAS

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    1. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
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    3. Cassar, Alessandra, 2007. "Coordination and cooperation in local, random and small world networks: Experimental evidence," Games and Economic Behavior, Elsevier, vol. 58(2), pages 209-230, February.
    4. Kirchkamp, Oliver & Nagel, Rosemarie, 2005. "Learning and cooperation in network experiments," Sonderforschungsbereich 504 Publications 05-27, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    5. Berninghaus, Siegfried K. & Ehrhart, Karl-Martin & Keser, Claudia, 2002. "Conventions and Local Interaction Structures: Experimental Evidence," Games and Economic Behavior, Elsevier, vol. 39(2), pages 177-205, May.
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    Cited by:

    1. Edward Cartwright & Anna Stepanova, 2017. "Efficiency in a forced contribution threshold public good game," International Journal of Game Theory, Springer;Game Theory Society, vol. 46(4), pages 1163-1191, November.

    More about this item

    Keywords

    experimental economics; networks; learning;

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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