(3.238.173.209) 您好!臺灣時間:2021/05/16 21:43
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

: 
twitterline
研究生:池秉聰
論文名稱:人工雙方喊價市場之競價行為與市場績效的研究-遺傳規劃的應用
指導教授:陳樹衡陳樹衡引用關係
學位類別:碩士
校院名稱:國立政治大學
系所名稱:經濟學系
學門:社會及行為科學學門
學類:經濟學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:中文
中文關鍵詞:軟體代理人人工智慧電子商務人工雙方喊價市場議價代理人納許式過程分配效率價格效率
外文關鍵詞:Software AgentArtificial IntelligenceElectronic CommerceArtificial Double Auction MarketBargaining AgentNash-Like ProcessAllocative EfficiencyPrice Efficiency
相關次數:
  • 被引用被引用:2
  • 點閱點閱:206
  • 評分評分:
  • 下載下載:40
  • 收藏至我的研究室書目清單書目收藏:7
近年來,網際網路(Internet)快速發展,已成為一個無疆無界無時差的市場,如何不被這股潮流所淘汰,我們所提出的解決方案─軟體代理人(software agent),一位具有人工智慧(artificial intelligence)演化調適(adaptive)能力的代理人,現在已經有許多企業與資訊、管理、電腦科學等各方面專家結合,開始使用軟體代理人來代勞,試想一位永不停止、具有創新、學習適應的員工,企業家可以隨意複製或刪除,隨時配合市場規模,不必擔心任何裁員的負擔,這樣的代理人的問世,勢必對我們的經濟環境帶來莫大的衝擊。
電子商務(electronic commerce)已經行之有年,人類的消費型態似乎不易於因這個轉變而有所改變,消費者如果沒有經過視覺、觸覺、嗅覺等感官的刺激,很難有購買的動機,再加上授信制度的不健全使得電子商務的施行充滿了風險。雖然有這麼多問題,我們仍無法阻擋這股趨勢,在電子科技的進步,3D數位影像、各種感官刺激的傳送、或如同期貨市場上明確公認的規格、法律的修訂、完善的認證制度,接下來我們就是要看軟體代理人的表現。
我們將軟體代理人運用在人工雙方喊價(artificial double auction)的市場,就像真實市場已經有人開始使用自動下單或自動議價代理人的機制一樣。然而市場上是否有必然不敗的策略呢?本文就是要解開這個答案。再進一步來看,待真實市場每個成員受不了生存競爭的壓力,也採取使用代理人的演化性策略,屆時我們的人工市場就是真實市場的縮影,我們在本文也會針對這樣一個具有未來前瞻性市場的表現如何?透過經濟學的角度來揭露市場的本質是否仍然維持?
在本文軟體代理人即為議價代理人(bargaining agent),她可以在穩定的(stable)市場環境(其他參與者使用固定策略)中辨別出一些有利的市場特徵,藉由這些特徵發展出有利的策略,而其結果甚至不是很容易想到的策略;接著若每個人都使用議價代理人在市場上交易,這裡我們使用一種納許式過程(Nash-like process)來詮釋,之後再分別依市場的分配效率、價格效率、及所得分配來討論市場績效。
1 緒論
1.1 研究動機
1.1.1 為什麼看不到網路上有雙方喊價市場呢?
1.1.2 研究目的
1.1.3 研究限制: 基本問題
1.1.4 本文架構及研究方法
1.2 文獻回顧
1.3 聖塔菲雙方喊價市場
1.3.1 實驗雙方喊價市場
1.3.2 訊息
1.3.3 Token值產生過程
1.3.4 交易程序
2 人工智慧經濟學雙方喊價市場介紹
2.1 議價代理人
2.1.1 基本原素: 終點集合與函數集合
2.1.2 初始化
2.1.3 演化母體
2.1.4 適合度函數
2.1.5 選擇機制和遺傳運作元
2.1.6 複雜度的限制
2.1.7 納許式的過程
2.2 人工喊價市場之代理人基計算建模
2.2.1 市場環境介紹
2.2.2 實驗設計
2.2.3 基本統計量
3 市場結構與競價行為
3.1 GP交易者的行為符合理性嗎? 簡單的測試
3.2 行為假設
3.2.1 假設1: 有恃無恐策略
3.2.2 假設2: 捷足先登策略
3.3 基它策略的內涵
3.4 恐龍假設
4 市場績效
4.1 市場總實現比例
4.1.1 市場總實現比例的測度
4.1.2 測度期間及表現方式
4.2 價格效率
4.3 所得分配
4.4 市場收斂
4.4.1 影響市場收斂的因素
4.5 策略空間
5 結論與建議
附錄
參考文獻與書目
李富民,陳瑞斌,洪瑞文 (2000),"軟體代理人於網路拍賣與議價系統之應用",中華民國資訊學會通訊,第三卷,第二期, pp. 67-80.
Andrews, M. and R. Prager (1994), "Genetic Programming for the
Acquisition of Double Auction Market Strategies," in K. E. Kinnear (ed.), Advances in Genetic Programming, Vol. 1, MIT Press. pp. 355-368.
Arthur, W. Brian (1992), ''On Learning and Adaptation in the Economy,'''' A Working Paper from the SFI Economics Research Program.
Axelrod, R. (1984), The Evolution of Cooperation, Basic Books.
Beaufils, B., J.-P. Delahaye and P. Mathieu (1998),
''Complete Classes of Strategies for the Classical
Iterated Prisoner''s Dilemma,'''' in V. W. Porto, N.
Saravanan, D. Waagen, and A. E. Eiben (eds.),
Evolutionary Programming VII, pp. 33-42.
Chen, S.-H. and C.-C. Ni (2000), ''Simulating the Ecology of Oligopoly Games with
Genetic Algorithms,'''' Knowledge and Information Systems: An International Journal, 2000 (2), pp.310-339.
Chen, S.-H and C.-H. Yeh (2001), ''Evolving Traders and the
Business School with Genetic Programming: A New Architecture
of the Agent-Based Artificial Stock Market,'''' Journal of
Economic Dynamics and Control, Vol.25,pp.363-393.
Chen, S.-H. (2000), ''Toward an Agent-Based Computational Modeling of Bargaining Strategies in Double Auction Markets with Genetic Programming,'''' in K.S.Leung, L.-W.Chan,
and H.Meng (eds.), Intelligent Data Engineering and Automated Learning-IDEAL 2000: Data Mining, Financial Engineering, and Intelligent Agents, Lecture Notes in Computer
Sciences 1983, Springer, 2000, pp.517-531.
Chen, S.-H. (2001), ''Fundamental Issues in the Uses of Genetic Programming in Agent-Based Computational Economics,'''' AI-ECON Working Paper Series 2001-2.
Chen, S. -H. (2001) , ''Evolving Bargaining Strategies with Genetic Programming: An Overview of AIE-DA, Ver. 2 Part 1,''''
in Proceedings of Fourth International Conference on Computational Intelligence and Multimedia Applications(ICCIMA),
Yokusika City, Japan, Oct. 30 - Nov. 1, IEEE Computer Society Press.
Chen, S. -H., B. -T. Chie, and C. -C. Tai, (2001) ''Evolving Bargaining Strategies with Genetic Programming:
An Overview of AIE-DA, Ver. 2 Part 2,''''
in Proceedings of Fourth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA),
Yokusika City, Japan, Oct. 30 - Nov. 1, IEEE Computer Society Press.
Cliff, D. (1997), ''Minimal-Intelligence Agents for Bargaining
Behaviors in Market-Based Environments,'''' HP Technical Report,
HPL-97-91, 1997.
Dawid, H. (1999), ''On the Convergence of Genetic Learning in a Double Auction Market,'''' Journal of Economic Dynamics and Control, 23, pp. 1545-1567.
Dosi, G., L. Marengo, A. Bassanini, and M. Valente (1999),
''Norms as Emergent Properties of Adaptive Learning: The Case of Economic Routines,'''' Journal of Evolutionary Economics, 9(1), pp. 5--26.
Friedman, D. (1993),''The Double Auction Market Institution: A Survey'''', The Double Auction Market Institutions, Theories, and
Evidence, Proceedings of the workshop on double auction markets, proceedings vol. XIV, Addison-Wesley .
Duffy, J. and J. Engle-Warnick (2001), ''Using Symbolic Regression to Infer Strategies from Experimental Data,'''' in Chen, S.-H. (ed.), Evolutionary Computation in Economics
and Finance, Physica Verlag.
Geyer-Schulz A. (1997), Fuzzy Rule-Based Expert Systems and Genetic Machine Learning, 2nd edn. Physica-Verlag.
Gode, D. K., and S. Sunder(1993), ''Allocative Efficiency
of Market with Zero-Intelligence Trader: Market as a Partial
Substitute for Individual Rationality,'''' Journal of Political
Economy, Vol. 101, No. 1, pp. 119-137.
Hayek, F. A. (1945), ''The Use of Knowledge in Society.''''
American Economic Reiview, 34(4), pp. 519-530.
Holland J. (1997), Adaptation in Natural and Artificial System,
University of Michigan Press.
Kirman, A. P., and N. Vriend (2001), ''Evolving Market Structure: An ACE Model of Price Dispersion and Loyalty'''', Journal Of Economic Dynamics And Control,
(25)3-4, pp. 459-502.
Koza, J. R. (1992), Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press.
Koza, J. R. (1994), Genetic programming II : Automatic Discovery of Reusable Programs, MIT Press.
Ok, S. K. Miyashita and S. Nishihara (2000), ''Improve Performance of GP by Adaptive Terminal Selection,''''
PRICAI 2000.
Olsson, L. (2000), ''Evolution of Bargaining Strategies for
Continuous Double Auction Markets Using Genetic Programming,''''
forthcoming in Proeceedings of the First International
Workshop on Computational Intelligence in Economics and
Finance (CIEF''2000).
Rust, J., R. Palmer, and J. Miller (1993): ''Behaviour of
Trading Automata in a Computerized Double Auction Market,''''
in D. Friedman and J. Rust (eds.), The Double Auction
Market: Institutions, Theories, and Evidence, Addison Wesley.
Chap. 6, pp.155-198.
Rust, J., J. Miller, and R. Palmer (1994), ''Characterizing
Effective Trading Strategies: Insights from a Computerized
Double Auction Market,'''' Journal of Economic Dynamics and
Control, Vol. 18, pp.61-96.
Smith, V. (1962), ''An Experimental Study of Competitive
Market Behaviour,'''' Journal of Political Economy, 70, pp.111-137.
Smith, V. L., G. L. Suchanek, and A. Williams.(1988),
''Bubbles, Crashes, and Endogenous
Expectations in Experimental Spot Asset Markets,''''
Econometrica 56 pp. 1119-1151.
Smith, V. (1992), Papers in Experimental Economics, Cambridge
University Press.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top