Abstract
In this paper, genetic programming (GP) is employed to model learning and adaptation in the overlapping generations model, one of the most popular dynamic economic models. Using a model of inflation with multiple equilibria as an illustrative example, we show that our GP-based agents are able to coordinate their actions to achieve the Pareto-superior equilibrium (the low-inflation steady state) rather than the Pareto-inferior equilibrium (the high-inflation steady state). We also test the robustness of this result with different initial conditions, economic parameters, and GP control parameters.
This paper is an abbreviated version of Chen and Yeh (1998). Research support from NSC grant NSC. 86-2415-H-004-022 is gratefully acknowledged. The authors are grateful to David Fogel and one anonymous referee for painstaking reviews and many helpful suggestions. This paper is devoted to the memory of Mr. Paul Lin with Sun Fast International Corp., who had been a great supporter for our research for many years. To many people's grief, he died at the age of 38 on September 30, 1997 of liver cancer.
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References
Allais, M. (1947), “Economie et Interet,” Imprimerie Nationale, Paris.
Arifovic, J. (1995), “Genetic Algorithms and Inflationary Economies,” Journal of Monetary Economies, 36, pp. 219–243.
Arifovic, J. (1996), “The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies,” Journal of Political Economy, Vol. 104, No. 3, pp. 510–541.
Bullard, J. and J. Duffy (1994), “Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs,” mimeo, Federal Reserve Bank of St. Louis and University of Pittsburgh.
Chen, S.-H. and C.-H. Yeh (1996), “Genetic Programming Learning in the Cobweb Model,” in P. J. Angeline and K. E. Kinnear (eds.), Advances in Genetic Programming, Vol. II, MIT Press. pp. 443–466.
Chen, S.-H. and C.-H. Yeh (1998), “Modeling the Expectations of Inflation in the OLG model with Genetic Programming,” AI-ECON Research Group Working Paper Series No. 9801, Department of Economics, National Chengchi University.
Koza, J. R. (1992), Genetic Programming: On the Programming of Computers by Means of Natural Selection, Cambridge: MIT Press.
Lucas, R. E., Jr., (1986), “Adaptive Behavior and Economic Theory,” Journal of Business, 59, pp. 401–426.
Marimon, R. and S. Sunder (1994), “Expectations and Learning under Alternative Monetary Regimes: An Experimental Approach,” Economic Theory, 4, pp. 131–162.
Samuelson, P. A. (1958), “An Exact Consumption-Loan Model of Interest with or without the Social Contrivance of Money,” Journal of Political Economy, Vol. 66, No. 6, pp. 467–482.
Tesfatsion, L. (1996), “How Economists Can Get Alife,” in B. Arthur, S. Durlauf and D. Lane (eds.), The Economy as an Evolving Complex Systems, II, Santa Fe Institute in the Science of Complexity, Vol. XXVII, Addison-Wesley, Reading, MA. pp. 533–564.
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Chen, SH., Yeh, CH. (1998). Genetic programming in the overlapping generations model: An illustration with the dynamics of the inflation rate. In: Porto, V.W., Saravanan, N., Waagen, D., Eiben, A.E. (eds) Evolutionary Programming VII. EP 1998. Lecture Notes in Computer Science, vol 1447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0040833
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DOI: https://doi.org/10.1007/BFb0040833
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