A Model-to-model analysis of the repeated Prisoners' Dilemma : genetic algorithms vs. evolutionary dynamics
Vilà, Xavier (Vilà Carnicero) (Universitat Autònoma de Barcelona. Departament d'Economia i d'Història Econòmica)
Universitat Autònoma de Barcelona. Unitat de Fonaments de l'Anàlisi Econòmica
Universitat Autònoma de Barcelona. Institut d'Anàlisi Econòmica

Date: 2008
Description: 9 p.
Abstract: We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i. e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the analytical model. Our main conclusion is that analytical and computational models are good complements for research in social sciences. Indeed, while on the one hand computational models are extremely useful to extend the scope of the analysis to complex scenar.
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Language: Anglès.
Series: Working papers
Series: Working papers ; 747.08
Document: workingPaper
Subject: Jocs, Teoria de

Adreça alternativa: https://hdl.handle.net/2072/9954


9 p, 97.2 KB

The record appears in these collections:
Research literature > Working papers > Fundamentals Unit of the Economic Analysis. Working papers

 Record created 2009-07-15, last modified 2020-01-13



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