English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/1871
Share/Impact:
Statistics
logo share SHARE   Add this article to your Mendeley library MendeleyBASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:

Title

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

AuthorsCasari, Marco
KeywordsBounded rationality
Experiments
Common-pool resources
Genetic algorithms
Issue DateOct-2002
SeriesUFAE and IAE Working Papers
542.02
AbstractIt 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.
URIhttp://hdl.handle.net/10261/1871
Appears in Collections:(IAE) Informes y documentos de trabajo
Files in This Item:
File Description SizeFormat 
54202.pdf237,94 kBAdobe PDFThumbnail
View/Open
Show full item record
Review this work
 


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.