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Title: Agent-Based Modeling of Macroeconomics: Applications of Genetic Programming
Authors: 葉佳炫
Yeh, Chia-Hsuan
Contributors: 陳樹衡
Yeh, Chia-Hsuan
Date: 1999
Issue Date: 2009-09-18 17:20:51 (UTC+8)
Abstract: 本論文是承續有限理性總體經濟學發展下的一支研究。在傳統經濟分析上,
By means of the development of evolutionary computation, we have the chance to analyze economic system by relaxing the representative agent assumption. The important phenomena in economy, coordination and coevolution, can be observed and studied in the framework. However, this can't be done in traditional analytical methods.
From the agent-based point of view, we can understand why and how the coordination succeeds (or fails), and how the environment factors influence the economic dynamic process. Furthermore, we can see that the representative agent could be evolved. That means the representative agent is a result of evolution rather than proper assumption. Also, it doesn't guarantee that the representative agent is a natural result.
The technique used in this dissertation is genetic programming (GP). The introduction about genetic programming is given briefly. The economic interpretations of using genetic programming are also detailed.
From the simulations results, we can observe that the issues unsolved in macroeconomics, convergence of equilibrium in a heterogeneous agents environment and the equilibrium selection, can be analyzed. Moreover, our GP-based learning agents can replicate the results obtained from laboratory experiments with human subjects. The rich dynamic phenomena are also observed in the simulations. Theses motivate us to rethink about the role of learning behavior in economic system and the concept of equilibrium.
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