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Limited memory can be beneficial for the evolution of cooperation

Author

Listed:
  • Friederike Mengel

    () (Universidad de Alicante)

  • Gergely Horváth

    () (Dpto. Fundamentos del Análisis Económico)

  • Jaromir Kovarik

    (Universidad de Alicante)

Abstract

We study a dynamic process where agents in a network interact in a Prisoner’s Dilemma. The network not only mediates interactions, but also information: agents learn from their own experience and that of their neighbors in the network about the past behavior of others. Each agent can only memorize the last h periods. Evolution selects among three preference types: altruists, defectors and conditional cooperators. We show - relying on simulation techniques - that the probability of reaching a cooperative state does not relate monotonically to the size of memory h. In fact it turns out to be optimal from a population viewpoint that there is a finite bound on agents’ memory capacities. We also show that it is the interplay of local interactions, direct and indirect reputation and memory constraints that is crucial for the emergence of cooperation. Taken by itself, none of these mechanisms is sufficient to yield cooperation.

Suggested Citation

  • Friederike Mengel & Gergely Horváth & Jaromir Kovarik, 2010. "Limited memory can be beneficial for the evolution of cooperation," Working Papers. Serie AD 2010-25, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  • Handle: RePEc:ivi:wpasad:2010-25
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    File URL: http://www.ivie.es/downloads/docs/wpasad/wpasad-2010-25.pdf
    File Function: Fisrt version / Primera version, 2010
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    More about this item

    Keywords

    evolution; reputation; bounded memory; cooperation.;

    JEL classification:

    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • 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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