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An Analysis of a Simple Reinforcement Dynamics: Learning to Play an "Egalitarian" Equilibrium

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  • Possajennikov, A.

    (Tilburg University, Center for Economic Research)

Abstract

The paper analyses a simple reinforcing dynamics. The dynamics can be interpreted as a learning dynamics with fixed aspiration level. All payoffs are assumed to be above this aspiration level, therefore all strategies are reinforcing. Different versions of the dynamics exhibit different convergence properties. The analysis starts with one-agent decision problems and proceeds to games. Some results are available for decision problems and simple games. For complex games computer simulations are performed. The hypothesis is that the dynamics favors an "egalitarian" equilibrium even if it does not satisfy other refinements.

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Bibliographic Info

Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1997-19.

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Date of creation: 1997
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Handle: RePEc:dgr:kubcen:199719

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Web page: http://center.uvt.nl

Related research

Keywords: Equilibrium selection; stochastic learning; bounded rationality;

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  1. Richard J. Herrnstein & Drazen Prelec, 1991. "Melioration: A Theory of Distributed Choice," Journal of Economic Perspectives, American Economic Association, vol. 5(3), pages 137-156, Summer.
  2. Gale, John & Binmore, Kenneth G. & Samuelson, Larry, 1995. "Learning to be imperfect: The ultimatum game," Games and Economic Behavior, Elsevier, vol. 8(1), pages 56-90.
  3. Arthur, W Brian, 1993. "On Designing Economic Agents That Behave Like Human Agents," Journal of Evolutionary Economics, Springer, vol. 3(1), pages 1-22, February.
  4. repec:att:wimass:9325 is not listed on IDEAS
  5. Bendor, J. & Mookherjee, D. & Ray, D., 1994. "Aspirations, adaptive learning and cooperation in repeated games," Discussion Paper 1994-42, Tilburg University, Center for Economic Research.
  6. A. Roth & I. Er’ev, 2010. "Learning in Extensive Form Games: Experimental Data and Simple Dynamic Models in the Intermediate Run," Levine's Working Paper Archive 387, David K. Levine.
  7. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
  8. Martin Posch, 1997. "Cycling in a stochastic learning algorithm for normal form games," Journal of Evolutionary Economics, Springer, vol. 7(2), pages 193-207.
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