Integration of Path-Dependency in a Simple Learning Model: The Case of Marine Resources
AbstractOverexploitation 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
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Bibliographic InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 43 (2014)
Issue (Month): 2 (February)
Natural resources; Agent-based simulation; Roth–Erev model; Incomplete information; Bioeconomic model of fishery;
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