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.
International Conference on Evolutionary Programming EP 1998: Evolutionary Programming VII pp 829-838