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Evolutionary Dynamics in Public Good Games

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  • Christiane Clemens
  • Thomas Riechmann

Abstract

This paper explores the question whether boundedly rational agents learn to behave optimally when asked to voluntarily contribute to a public good. The dynamic game is described by an Evolutionary Algorithm, which is shown to extend the applicability of ordinary replicator dynamics of evolutionary game theory to problem sets characterized by finite populations and continuous strategy spaces. We analyze the learning process of purely and impurely altruistic agents and find in both cases the contribution level to converge towards the Nash equilibrium. The group size, the degree of initial heterogeneity and the propensity to experiment are key factors of the learning process. Copyright Springer Science+Business Media, Inc. 2006

Suggested Citation

  • Christiane Clemens & Thomas Riechmann, 2006. "Evolutionary Dynamics in Public Good Games," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 399-420, November.
    • Handle: RePEc:kap:compec:v:28:y:2006:i:4:p:399-420
    DOI: 10.1007/s10614-006-9044-4
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    References listed on IDEAS

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    Cited by:

    1. Ludo Waltman & Nees Eck & Rommert Dekker & Uzay Kaymak, 2011. "Economic modeling using evolutionary algorithms: the effect of a binary encoding of strategies," Journal of Evolutionary Economics, Springer, vol. 21(5), pages 737-756, December.
    2. Feng, Sinan & Liu, Xuesong & Dong, Yida, 2022. "Limited punishment pool may promote cooperation in the public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    3. Jaroslaw Stanczak, 2009. "Application of an evolutionary algorithmto simulation of the co2 emission permits marketwith purchase prices," Operations Research and Decisions, Wroclaw University of Technology, Institute of Organization and Management, vol. 4, pages 94-108.
    4. Pedro, de Mendonça, 2009. "Self-Enforcing Climate Change Treaties: A Generalized Differential Game Approach with Applications," MPRA Paper 17889, University Library of Munich, Germany.
    5. Hanauske, Matthias & Kunz, Jennifer & Bernius, Steffen & König, Wolfgang, 2010. "Doves and hawks in economics revisited: An evolutionary quantum game theory based analysis of financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 5084-5102.
    6. Kim Bloomquist, 2011. "Tax Compliance as an Evolutionary Coordination Game: An Agent-Based Approach," Public Finance Review, , vol. 39(1), pages 25-49, January.
    7. Jarosław Stańczak, 2009. "Application of an evolutionary algorithm to simulation of the CO2 emission permits market with purchase prices," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 19(4), pages 93-108.
    8. repec:wut:journl:v:4:y:2009:p:94-108:id:148 is not listed on IDEAS

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