Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/36157


Title: Agent-Based Modeling of Macroeconomics: Applications of Genetic Programming
Authors: 葉佳炫
Yeh, Chia-Hsuan
Contributors: 陳樹衡
葉佳炫
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,
許多不合理的假設可以藉由演化性計算的工具而得以放鬆,例如代表性個人
假設。這個特性,使我們可以更為真實地面對與分析經濟體系中非常重要的
兩個現象,即整合(coordination)與共演化(coevolution)。
而近來發展快速的agent-based計算經濟學,便在這個領域中異軍突起。在
agent-based的架構中,我們可以瞭解群體間(異質性個人)如何或為何(無法)
達成共識,以及環境因素如何影響到經濟動態的過程。而這樣的分析,卻是
在傳統的架構中難以做到的。同時,亦可以認知到代表性個人只是動態過程
中一個可能發生的現象。無人可以確保它的成立與否,即便出現,也無法得
知它是否可以長久維持。
在本論文中,我們採用演化性計算中的一個工具,遺傳規畫,來架構agent-based
的經濟環境。我們除了對於有限理性的發展作一概述外,並對這個分析工具
的方法論及經濟意涵提出了我們的看法。
在這樣的一個環境中,總體經濟領域裡兩個尚未解決的議題,即均衡的收斂
與均衡選擇,能得到較為清楚的答案與方向。從多次的模擬結果中顯示,以
遺傳規畫為學習方式的行為人所產生的群體動態過程,與我們在實驗經濟學
中所觀察到的相當類似。而在實驗室中,所觀察到豐富的互動過程,亦可以
在我們的模擬中發現。這樣的研究,使我們重新思考學習行為在經濟學中所
扮演的角色,以及傳統經濟學中所探討均衡的概念。
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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Description: 博士
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