|Abstract: ||本研究計劃旨在對代理人基計算經濟學(agent-based computational economics)之現行發展，做出基礎面及應用面之貢獻。基礎面向之課題，在本研究計劃中以「代理人工程」統稱之；應用面向之課題，即本計劃中所稱之「市場設計」。然而，此二課題並非獨立無關，本計劃將依據計算力對等(computational equivalence)法則，完成一個整合軟體代理人與真人的市場平台，做為一個能夠體現並處理市場設計複雜性的工具。於此研究中，我們嘗試將盧卡斯與賽門的論述加以結合，提出一個可以做為代理人工程的新原則，即「計算力對等」原則，並著手建立符合此一原則的實驗室－CE Lab。此實驗室將使軟體代理人與真人能共存於同一市場平台中，進而整合代理人基計算經濟學與實驗經濟學這兩塊關係甚密的研究領域。CE Lab的建構基礎有二，皆延續本研究團隊歷年來所累積之成果。其一是代理人基計算經濟學的模型及軟體，特別是AIE-DA與AIE-AFM；其二則是以網際網路作為架構的線上實驗市場平台—政大“事件期貨”交易市場(AI-ECON Futures Exchange, AI-ECON FX)。在過去的一年中，我們將現有的規模加以擴充。在AI-ECON FX中加入軟體代理人的部分，並已於北高兩市市長選舉中做過初步測試。在本次實驗中，我們累積了相當龐大的交易資料，於是我們引入了研究複雜網路的方法，試圖來分析市場中交易者的行為模式及其互動後所突現的現象。我們相信這項研究的結果將對軟體代理人建模及市場設計有所助益。|
The purpose of this research project is two-fold. First, we would like to contribute to one of the foundation aspects of the agent-based computational economics (ACE), known as agent engineering; second, from there, we would then extend our contribution to enhance the validity and robustness of market design.In this research project, as mainly motivated by Simon, attempts to materialize Lucas‘ suggestion by establishing a laboratory where human subjects are equipped with the computational power that satisfies the computational equivalence condition. The ultimate objective of this research project is to build up a laboratory in accordance with the proposed computational equivalence (CE) principle. The lab, called the CE Lab, can integrate agent-based computational economics and experimental economics into a coherent body so as to enrich our understanding of the markets comprising of both human agents and software agents, and provide a foundation of agent engineering. The CE Lab is built upon the extensions of two existing simulation platformsdeveloped by our research team. One, from the side of agent-based computational economics,comprises the double-auction market software, AIE-DA, and the artificial stock marketsoftware, AIE-ASM. The other, from the side of experimental economics, is the on-lineweb-based experimental market platform, AI-ECON FX (AI-ECON Futures Exchange).In the past year, we have expanded the current version of the platform. We have integrated software agents into AI-ECON FX and tested its performance in the provincial city mayor‘s election last year. We have accumulated huge transaction data in the experiment this time. Therefore, we introduce the method of the complex network study, trying to analyze the behavioral model of the traders in the market and the emergent phenomena after the interaction. We believe that this result shall help us in modeling the software agents and in the market design.