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Can genetic algorithms explain experimental anomalies? An application to common property resources

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dc.creator Casari, Marco
dc.date 2007-11-06T08:23:43Z
dc.date 2007-11-06T08:23:43Z
dc.date 2002-10
dc.date.accessioned 2017-01-31T00:58:03Z
dc.date.available 2017-01-31T00:58:03Z
dc.identifier http://hdl.handle.net/10261/1871
dc.identifier.uri http://dspace.mediu.edu.my:8181/xmlui/handle/10261/1871
dc.description It is common to find in experimental data persistent oscillations in the aggregate outcomes and high levels of heterogeneity in individual behavior. Furthermore, it is not unusual to find significant deviations from aggregate Nash equilibrium predictions. In this paper, we employ an evolutionary model with boundedly rational agents to explain these findings. We use data from common property resource experiments (Casari and Plott, 2003). Instead of positing individual-specific utility functions, we model decision makers as selfish and identical. Agent interaction is simulated using an individual learning genetic algorithm, where agents have constraints in their working memory, a limited ability to maximize, and experiment with new strategies. We show that the model replicates most of the patterns that can be found in common property resource experiments.
dc.description Financial support from the Division of the Humanities and Social Sciences at Caltech and the EU Marie Curie Fellowship is gratefully acknowledged.
dc.description Peer reviewed
dc.language eng
dc.relation UFAE and IAE Working Papers
dc.relation 542.02
dc.rights openAccess
dc.subject Bounded rationality
dc.subject Experiments
dc.subject Common-pool resources
dc.subject Genetic algorithms
dc.title Can genetic algorithms explain experimental anomalies? An application to common property resources
dc.type Documento de trabajo


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