臺灣博碩士論文加值系統

本研究的主要目的在於實作線上互動式議價機制，且買方能即時的得到議價的結果。本研究根據MVC設計模式提出一個智慧型代理人的議價系統架構，結合了模糊專家系統的技術，在實作的過程中，我們根據智慧型代理人的設計原則，定義代理人在議價系統中應具備的四項智能：反應、計算、判斷、決策，為了讓代理人實現這四項智能我們使用物件導向程式語言JAVA作為本研究的系統開發工具，並使用UML作為系統分析與設計的工具，開發了模糊專家系統並以軟體工程的觀點將其模組化。本研究所開發的模糊專家系統模組也經過與商業軟體FIDE數據誤差的驗證後，證實是可用的。本文並利用模糊專家模組建置一個電子商務網站，在網站裡所實現的是根據本文所設計的智慧型議價代理人系統，包含了賣方代理人、買方代理人以及中介議價協商代理人，經過買賣雙方進行買賣的模擬與購買價格滿意度測試，發現買方對於商品的購買價格的滿意度是高的並能得到及時性的互動議價結果，符合本研究的系統設計目標。

The purpose of this study is to implement an online price negotiation system where a buyer can conduct a price negation process with a seller and instantly get his negotiated price. Based on the Model-View-Controller (MVC) design pattern, we designed an intelligent agent-based system for price negotiation using a fuzzy expert system. During implementing the system, we followed the principles of designing intelligent agents with four abilities: reaction, computation, judgment, and decision. We used Unified Modeling Language (UML) as the system analysis and design tool. We also designed a computer package to implement the fuzzy expert system using Java programming language. The computer package is modularized into different components based on the software engineering theory. The fuzzy expert system has been validated by an existing commercial software package within an error rate of 2 percent. Finally, we established an e-commerce website for trading merchandises with the proposed price negotiation system. Three intelligent agents were built for the price negation system including a seller agent, buyer agent, and mediator agent. We also conducted an experiment to evaluate the satisfactions of using the price negotiation system. The evaluation results showed that the users have high satisfactions in their trading prices obtained by the proposed system.

第一章 導論 1
1.1研究背景 1
1.2研究動機與目的 2
1.3問題描述 2
1.4研究方法概述 3
1.5論文貢獻 4
1.6論文架構 4
第二章 文獻探討 5
2.1 智慧型代理人 5
2.2代理人在電子商務上的應用 10
第三章 智慧型議價代理人系統設計 15
3.1交易模式 15
3.2 MVC設計模式 17
3.2.1系統架構 19
第四章 模糊推論核心模組設計與實作 26
4.1 模糊理論 26
4.1.1 隸屬函數(Membership Function) 26
4.1.2 模糊法則 28
4.1.3 模糊推論 29
4.1.4 解模糊化 31
4.2 UNIFIED MODELING LANGUAGE(UML)統一塑模語言 32
4.3 模糊推論模組分析與設計 33
4.3.1 系統需求分析與設計 34
4.3.2 程式類別分析設計與整合 35
4.3.3 執行程序分析與設計 38
4.4 模糊推論模組與FIDE測試比較 41
4.4.1 兩個輸入一個輸出三個輸入參數 41
4.4.2 三個輸入一個輸出三個輸入參數 43
4.4.3 三個輸入一個輸出五個輸入參數 46
4.4.4 實驗測試結論 49
第五章 買賣雙方議價機制的建構與中介協商互動模式 50
5.1 議價機制 50
5.1.1 賣方代理人系統機制 51
5.1.2 買方代理人系統機制 53
5.2 中介議價協商代理人機制 55
5.3 系統整合與實現 57
第六章 實驗與結果分析 60
6.1 賣方代理人與買方代理人使用者介面 62
6.2 結果與分析 65
第七章 結論與未來展望 67
7.1 結論 67
7.2 未來展望 68
參考文獻 69

Amberjack Software LLC, (2002). JSP Insider, Retrieved 07 04, 2008, from http://www.jspinsider.com/content/jsp/struts/struts.jsp.
Amin, M., Ballard, D., (2000). Defining new markets for intelligent agents, IT Professional, vol. 2-4, pp. 29-35.
Aptronix, (2000). I.D.E Power Design Tool, Retrieved 06 18, 2008 from http://www.aptronix.com/fide/fide.htm.
Billsus, D. & Pazzani, M., (1998). Learning Collaborative InformationFilters, Proc. 15th Int’l Conf. Machine Learning, pp. 46-54.
Brustolini, J.C. (1991). Autonomous Agents: Characterization and Requirements, Report CMU-CS-91-204, School of Computer Science, Carnegie-Mellon University, Pittsburgh.
Cheng, C.-B., Chan, C.-C. H., & Lin, K.-C., (2006). Intelligent agents for e-marketplace: Negotiation with issue trade-offs by fuzzy inference systems. Decision Support Systems, 42(2), pp. 626-638.
Cheung, W. K., & Hsu, J. Y., (2007). Intelligent agents in e-services. Electronic Commerce Research and Applications, 6(4), pp. 367-368.
Coen, M.H. (1995). SodaBot: A Software Agent Construction System, MIT AI Lab, USA.
Cortex Site (2007), Cortex Intelligence Demonstration of Web 3.0, December 6, 2007 retrieved from http://www.cortex-intelligence.com/tech/.
Dastani, M., Jacobs, N., Jonker, C.M., Treuer, J., (2001). Modeling User Preferences and Mediating Agents in Electronic Commerce, Agent Mediated Electronic Commerce, F. Dignum & C. Sierra, eds., pp. 163-193.
Foss, J., (1998). Brokering the Info-Underworld, British Telecommunications Eng., vol. 17, no. 2, pp. 202-206.
Franklin S. P., Graesser A.G.. (1996). Is It an Agent, or Just a Program? : A Taxonomy for Autonomous Agents, In: Intelligent Agents III, J.P. Muller, M.J. Wooldridge & N. R. Jennings (Eds.), Springer-Verlag, Heidelberg.
Fujishima, Y., Leyton-Brown, K., Shoham, Y., (1999). Taming the Computational Complexity of Combinatorial Auctions: Optimal and Approximate Approaches, Proc. 16th Int’l Joint Conf. Artificial Intelligence, pp. 548-553.
Gilbert, D., Aparicio, M., Atkinson, B., Brady, S., Ciccarino, J., Grosof, B., O’Connor, P., Osisek, D., Pritko, S., Spagna,R. & Wilson, L. (1995). IBM Intelligent Agent Strategy, White Paper.
Guttman, R. H., Moukas, A. G.., & P. Maes, (1998). Agent-Mediated Electronic Commerce: A Survey, The Knowledge Eng. Rev., vol. 13,no. 2, pp. 147-159.
Hayes-Roth, B., Pfleger, K., Lalanda, P., Morignot, P. & Balabanovic, M., (1995). A Domain Specific SoftwareArchitecture for Adaptive Intelligent Agents, IEEE Transactions on Software Engineering, 21(4), pp.288-301.
He, M., Jennings, N. R., Leung, H-F., (2003). On Agent-Mediated Electronic Commerce, IEEE Transaction on Knowledge and Data Engineering, vol.15, no.4.
Holland, J. H., (1975). Adaptation in Natural and Artificial Systems, University of Michigan Press.
Jeffrey Zeldman (2006). Web 3.0. January 16, 2006 retrieved from http://www.alistapart.com/articles/web3point.
Jennings, N. R., Faratin, P., Johnson, M. J., Norman, T. J., O'Brien, P., Wiegand, M. E (1996b). Agent-based businessprocess management, International Journal of Cooperative Information Systems, 5 (2&3), pp. 105-130.
Jennings, N. R., Faratin, P., Lomuscio, A.R., Parsons, S., Sierra, C., Wooldridge, M., (2001). Automated Negotiation: Prospects, Methods and Challenges, Int. J. Group Decision and Negotiation, vol. 10, no. 2, pp. 199-215.
Jennings, N. R., Mamdani, E. H., Corera, J., Laresgoiti, I., Perriolat F., Skarek, P. & Varga, L. Z. (1996a). UsingARCHON to develop real-word DAI applications, IEEE Expert, 11 (6), pp. 64-70.
Jung, J., Jo, G.., (2000). Brokerage between Buyer and Seller Agents Using Constraint Satisfaction Problem Models, Decision Support Systems, vol. 28, pp. 293-304.
Kandel, A. (1992). Fuzzy Expert Systems, CRC Press, Boca Raton, pp. 8-19.
Khosla R., Kitjongthawonkul, S., (2001). A Human-Centered Agent-Based Architecture for Electronic Brokerage, Soft Computing, vol. 6, pp. 405-411.
Krulwich, B. (1996). The Bargainfinder Agent: Comparison Price Shopping on the Internet, Bots, and Other Internet Beasties, J. Williams, ed., Macmillan Computer Publishing, pp. 257-263.
Kumar, K. (2001). Technology for Supporting Supply-Chain Management, Comm. ACM, vol. 44, no. 6, pp. 58-61.
KurzweilAI.net (2006). Nova Spivack The Third-Generation Web is Coming, December 17, 2006 retrieved from http://www.kurzweilai.net/meme/frame.html?main=/articles/art0689.html.
Ljungberg, M., Lucas, A., (1992). The OASIS Air Traffic Management System, Proceedings of the Second Pacific Rim International Conference on Artificial Intelligence, PRICAI ’92, Seoul, Korea.
Maes, P., (1995). Artificial Life Meets Entertainment: Lifelike Autonomous Agents, Communications of the CAN, Special Issue on Novel Applications of AI.
Mamdani, E. H., (1974). Applications of fuzzy algorithms for control of simple dynamic plants, IEEE Proceedings, pp. 1585-1588.
Manvi, S. S., Venkataram, P., (2005). An intelligent product-information presentation in E-commerce. Electronic Commerce Research and Applications, 4(3), pp.220-239.
Montano, B. R., Yoon, V., Drummey, K., Liebowitz, J., (2008). Agent learning in the multi-agent contracting system [MACS]. Decision Support Systems, 45(1), pp.140-149.
MRK, T. Magedanz, K. Rothermel, S. Krause, (1996). Intelligent Agents:An EmergingTechnology for Next Generation Telecommunication? In proceeding of IEEEINFOCOM*96, pp. 464-472.
Murch R., Johnson, T., (1999). Intelligent Software Agents, chapter 14, Upper Saddle River, N.J.: Prentice HallPTR. pp. 131-137.
Object Management Group. (2008). Unified Modeling Language, Retrueved 07 04, 2008, from http://www.uml.org/
Rassenti, S., Smith, V., Bulfin, R., (1982). A Combinatorial Auction Mechanism for Airport Time Slot Allocation, Bell J. Economics, vol. 13, no. 2, pp. 402-417.
Ribeiro, R. A., (1996). Fuzzy Multiple Attribute Decision Making: A Review and New Preference Elicitation Techniques, Fuzzy Sets and Systems, vol. 78, pp. 155-181.
Rosenschein, J. S., Zlotkin, G. (1994). Rules of Encounter. The MIT Press.
Rudowsky, I., (2004). Intelligent Agents, Proceedings of the Americas Conference on Information Systems, New York.
Russell, S., Norvig, P., (1995). Artificial Intelligence: A Modern Approach, Prentice-Hall, Englewood Cliffs, NJ.
Search Engine News (2006), Terri Wells Web 3.0 and SEO, November 29, 2006 retrieved from http://www.seochat.com/c/a/Search-Engine-News/Web-30-and-SEO/.
Shehory O., Kraus, S., (1998). Methods for Task Allocation via Agent Coalition Formation, Artificial Intelligence, vol. 101, pp. 165-200.
Sun Microsystems, (2002). Java BluePrints Model-View-Controller, Retrieved 07 04, 2008, from http://java.sun.com/blueprints/patterns/MVC-detailed.html.
Sycara, K.P., (1998). Multiagent Systems, Artificial Intelligence, pp. 79-92.
Turban, J. Lee, D. King, Chung, H. M., (1999). Electronic Commerce: A Managerial Perspective, E. Prentice Hall.
Woodridge, M., Jennys, N. R. (1995). Intelligent agents: theory and practice. The Knowledge Engineering Review, 10(2), pp.115-152.
Wooldridge, M., ( 2002). An Introduction to MultiAgent Systems, Wiley, England.
Wooldridge, M., Jennings, N.R., (1995). Intelligent Agents: Theory and Practice, The Knowledge Engineering Review, 10(2), pp.115-152.
Xu, D., & Wang, H., (2006). Intelligent agent supported personalization for virtual learning environments. Decision Support Systems, 42(2), pp.825-843.
Zadeh, L. A., (1965). Fuzzy sets, Information and Control, vol. 8, no. 3, pp. 338-353.
Zadeh, L. A., (1988). Fuzzy logic, IEEE Computer, pp. 83-93.