Abstract
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, GP control parameters,
and the selection mechanism. We find that as long as
the survival-of-the-fittest principle is maintained,
the evolutionary operators are only secondarily
important. However, once the survival-of-the-fittest
principle is absent, the well-coordinated economy is
also gone and the inflation rate can jump quite wildly.
To some extent, these results shed light on the
biological foundations of economics.
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