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



decentralized sanctioning system were run but not reported in this study. Such simulation
results match many of the experimental data pattern reported in Casari and Plott (2003).

To conclude, we find that genetic algorithm agents exhibit many of the same patterns
observed in common property resource experiments. Alongside its evolutionary nature, the
ability to generate individually distinct patterns of behavior originating from identical goals
and identical rationality levels may be the most interesting feature of an individual learning
genetic algorithm.

19



More intriguing information

1. The name is absent
2. Informal Labour and Credit Markets: A Survey.
3. Real Exchange Rate Misalignment: Prelude to Crisis?
4. Who’s afraid of critical race theory in education? a reply to Mike Cole’s ‘The color-line and the class struggle’
5. MANAGEMENT PRACTICES ON VIRGINIA DAIRY FARMS
6. Subduing High Inflation in Romania. How to Better Monetary and Exchange Rate Mechanisms?
7. SOME ISSUES IN LAND TENURE, OWNERSHIP AND CONTROL IN DISPERSED VS. CONCENTRATED AGRICULTURE
8. The name is absent
9. The name is absent
10. Public-Private Partnerships in Urban Development in the United States
11. Strategic Policy Options to Improve Irrigation Water Allocation Efficiency: Analysis on Egypt and Morocco
12. Gender and headship in the twenty-first century
13. BODY LANGUAGE IS OF PARTICULAR IMPORTANCE IN LARGE GROUPS
14. Education Research Gender, Education and Development - A Partially Annotated and Selective Bibliography
15. REVITALIZING FAMILY FARM AGRICULTURE
16. Parent child interaction in Nigerian families: conversation analysis, context and culture
17. Two-Part Tax Controls for Forest Density and Rotation Time
18. IMPLICATIONS OF CHANGING AID PROGRAMS TO U.S. AGRICULTURE
19. The name is absent
20. A Classical Probabilistic Computer Model of Consciousness