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Integration of Path-Dependency in a Simple Learning Model: The Case of Marine Resources

Author

Listed:
  • Nariné Udumyan

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Juliette Rouchier

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Dominique Ami

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

Overexploitation of renewable resources, and more particularly fisheries, is often driven by the lack of information about the state and dynamics of the resource. A solution to this problem stemming from the resource users is proposed in this paper. We use an agent-based model composed of a bio-economic model of Gordon-Schaefer where agents make choices following a very simple learning model. We modify the Roth-Erev learning model so that agents explain their profit not only by current action but also by past action. This modification radically changes the dynamics of the resource use, which turns out to be sustainable. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Nariné Udumyan & Juliette Rouchier & Dominique Ami, 2014. "Integration of Path-Dependency in a Simple Learning Model: The Case of Marine Resources," Post-Print hal-01463951, HAL.
    • Handle: RePEc:hal:journl:hal-01463951
    DOI: 10.1007/s10614-013-9375-x
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    Cited by:

    1. Utomo, Dhanan Sarwo & Onggo, Bhakti Stephan & Eldridge, Stephen, 2018. "Applications of agent-based modelling and simulation in the agri-food supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 794-805.

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