Article thumbnail

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

By Marco Casari


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.Bounded rationality, Experiments, Common-pool resources, Genetic algorithms

OAI identifier: oai:RePEc:aub:autbar:542.02

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.

Suggested articles


  1. (2000). Agent-based Computational Finance: Suggested Readings and Early Research,”
  2. (2000). An Illustration of the Essential Difference between Individual and Social Learning, and its Consequences for Computational Analysis,
  3. (1997). Anomalous Behavior in Public Goods Experiments: How Much and Why?.
  4. (1991). Artificial Adaptive Agents
  5. (1995). Auction with
  6. (1997). Behavioural Heterogeneity and Genetic Algorithm Learning in the Cobweb Model,” IKSF - Institut für Konjunktur-
  7. (1991). Can Evolutionary Dynamics Explain Free Riding Experiments?”
  8. (1996). Computer mediated communication and the emergence of ‘electronic opportunism,’ ” Working paper 1996-01,
  9. (2000). Computer Testbeds and Mechanism Design: Application to the Class of Groves-Ledyard Mechanisms for Provision of Public Goods,” manuscript,
  10. (2001). Cooperation and noise in public goods experiments: applying the contribution function approach,”
  11. (2003). Decentralized Management of a Common Property Resource: Experiments with Centuries-Old Institutions,”
  12. (1996). Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms,
  13. (1994). Genetic algorithm learning and the cobweb model,”
  14. (1999). Learning and Behavioral Stability: An economic interpretation of genetic algorithms,”
  15. (1990). Mathematical Bioeconomics. The Optimal Management of Renewable Resources,
  16. (1998). Modeling bounded rationality,
  17. (1990). Money as a medium of Exchange in an
  18. (1999). On the Convergence of Genetic Learning in a Double Auction Market,”
  19. (1990). Rent Dissipation in a Limited-Access CommonPool Resource: Experimental Evidence,”
  20. (1994). Rules, Games, and Common-Pool Resources, Ann Arbor,
  21. (1995). The ‘Spite’ Dilemma in Voluntary Contribution Mechanism Experiments.
  22. (1996). The behavior of the exchange rate in the genetic algorithm and experimental economies,”
  23. (1954). The economic theory of a common property resource: the fishery,”
  24. (1998). The evolution of type communication in a sender/receiver game of common interest with cheap talk,”
  25. (1995). The Handbook of experimental economics,
  26. (1998). Voluntary Provision of Public Goods: Experimental Results with Interior Nash Equilibria,”