协商理论在敏捷制造系统中的应用研究
|
摘要
协商(Negotiation)是人际互动模式中最复杂的一种沟通方式。协商系统就是人们为了实现协商过程，借助计算机技术和网络技术等信息技术，构建的一个协商体系结构，用于完成协商过程中的所有活动。敏捷制造环境下的企业必须具有快速重组能力，在重组的过程中难免产生资源冲突或利益冲突，这就需要协调，而协商是解决冲突最有效的协调方式。本文围绕协商理论在敏捷制造系统中的应用问题展开研究，主要研究工作如下：
研究了Agent的概念，Multi-Agent系统结构、通讯语言等相关技术，构建了基于Agent的自动协商系统框架。分析了目前比较前沿的博弈论协商、启发式协商、说服式协商和基于机器学习技术的协商理论及其各自的优缺点，研究了支持自动协商的关键技术问题：多协商任务的自动化执行技术、协商协议的定义及形式化描述，以及协商协议和协商内容的知识共享问题。
分析了敏捷制造环境下企业之间合作-竞争的关系，构建了基于“双赢”协商的敏捷供应链管理系统，重点研究了系统中的“双赢”协商模型。分析了传统多属性协商模型存在的效用计算和协商偏好信息完备问题，对效用计算公式进行了合理化的修正，提出了解决偏好信息不完备条件下实现“双赢”协商的技术方案以及基于神经网络学习技术的自适应协商策略，并进行了实验分析验证。
分析了传统的基于整数规划法的重构算法不能反映敏捷制造的动态性特征的局限性，建立了基于协商的重构算法数学模型。在此基础上，提出了基于CNCP扩充网协商协议的自组织招标的网络资源集成方案，并对集成方案采用遗传算法进行了优化，对优化方案实施二次招标以考证优化方案的可行性。实验结果表明，通过协商进行系统重构的方法是科学合理的，体现了敏捷制造动态性色彩。
分析了敏捷制造环境下企业之间的合作关系，构建了通过经济赔偿而由承担后续加工任务的成员赶上生产进度的控制系统模型。重点研究了一对多(多个紧后任务)“赔偿式”协商模型，基于“多赢”协商的思想，通过等效用插值法，建立了统一约束协商属性下各方协商的策略。对于经典的工期-费用协商问题，进行了模拟实验分析。
研究了JADE平台下Agent的黄页管理机制、ACL通讯语言，开发了敏捷供应链环境下企业物资采购协商系统、敏捷制造重构原型系统。
Negotiation is the most complicated mode of communication in human interaction models. In order to carry out the negotiation process, the negotiation system based on information technology such as computer and network technology is constructed as negotiation architecture to accomplish all activities in negotiation process. Under agile manufacturing mode, enterprises must have the capability of rapid reconfiguration, in which it is hard to avoid the conflicts of resources and interest and harmonizing is needed. Negotiation is the most effective way of harmonizing to solve the conflicts in this process. This paper is concerned with the research on the application of negotiation theory in Agile Manufacturing System. Main research work being carried out is as follows.
An Agent-based Framework of automated Negotiation has been constructed based on the theoretical discussion of the concept of Agent, the architecture of Multi-Agent System, communication language and related technology. After the advantages and disadvantages of some presently advanced theory such as negotiation on the Game Theory, heuristic negotiation, persuading negotiation and negotiation theory on machine learning is analyzed, The key technical problems to support automated negotiation, such as automatic execution technique of multi-task negotiation, the definition and formalization description of negotiation protocol, self-adapting of negotiation protocol and knowledge sharing problem in negotiation protocol and content ,etc. are studied.
An agile supply chain management system based on win-win negotiation is built up based on the analyzing of the relationship between competitions and co-operations among enterprises in agile manufacturing environment. The win-win negotiation model in the agile supply chain management system is studied mainly. After the problem of utility calculation and the problem of complete preferences information existing in conventional multi- issues negotiation model is systematically construed, the formula of utility computing is rationally modified, and the technique scheme which implements win-win negotiation under the condition of incomplete preferences information as well as self-adaptation negotiation strategy based on neural network learning technique are put forward, which are proved experimentally to be valid.
The mathematical model of reconfiguration algorithms based on negotiation has been advanced after the limitation not reflecting the dynamic character in Agile Manufacturing System in traditional reconfiguration algorithms based on integer programming is analyzed. A network resources integration scheme which can be realized by self-organization bidding based on the negotiation protocol of CNCP extension net is put forward. The integration scheme is optimized by using of genetic algorithm, and secondary biding is executed in order to obtain the feasibility of the optimization result. The experimental results indicate that: the method of system reconfiguration by negotiation is of scientific and suitable features, reflecting the dynamic character of agile manufacturing system.
With the systematic analysis of the co-operations relationship among enterprises in agile manufacturing environment, a control system model with the members taking the next machining task to catch up against the production schedule by economic compensation has been constructed, with its focus on the research of the one-to-more compensation negotiation model. The build-up of negotiation strategy under uniform restrained negotiation attributions is based on the idea of multiple-win using equal utility interpolation methods. The simulated experiment for classical time-cost negotiation problem is synthesized
Investigation has been carried out on Yellow page management mechanism of JADE platform and ACL communication language. Enterprise material purchasing negotiation system and agile manufacturing reconfiguration prototype system have been developed in agile manufacturing environment.
研究了Agent的概念，Multi-Agent系统结构、通讯语言等相关技术，构建了基于Agent的自动协商系统框架。分析了目前比较前沿的博弈论协商、启发式协商、说服式协商和基于机器学习技术的协商理论及其各自的优缺点，研究了支持自动协商的关键技术问题：多协商任务的自动化执行技术、协商协议的定义及形式化描述，以及协商协议和协商内容的知识共享问题。
分析了敏捷制造环境下企业之间合作-竞争的关系，构建了基于“双赢”协商的敏捷供应链管理系统，重点研究了系统中的“双赢”协商模型。分析了传统多属性协商模型存在的效用计算和协商偏好信息完备问题，对效用计算公式进行了合理化的修正，提出了解决偏好信息不完备条件下实现“双赢”协商的技术方案以及基于神经网络学习技术的自适应协商策略，并进行了实验分析验证。
分析了传统的基于整数规划法的重构算法不能反映敏捷制造的动态性特征的局限性，建立了基于协商的重构算法数学模型。在此基础上，提出了基于CNCP扩充网协商协议的自组织招标的网络资源集成方案，并对集成方案采用遗传算法进行了优化，对优化方案实施二次招标以考证优化方案的可行性。实验结果表明，通过协商进行系统重构的方法是科学合理的，体现了敏捷制造动态性色彩。
分析了敏捷制造环境下企业之间的合作关系，构建了通过经济赔偿而由承担后续加工任务的成员赶上生产进度的控制系统模型。重点研究了一对多(多个紧后任务)“赔偿式”协商模型，基于“多赢”协商的思想，通过等效用插值法，建立了统一约束协商属性下各方协商的策略。对于经典的工期-费用协商问题，进行了模拟实验分析。
研究了JADE平台下Agent的黄页管理机制、ACL通讯语言，开发了敏捷供应链环境下企业物资采购协商系统、敏捷制造重构原型系统。
Negotiation is the most complicated mode of communication in human interaction models. In order to carry out the negotiation process, the negotiation system based on information technology such as computer and network technology is constructed as negotiation architecture to accomplish all activities in negotiation process. Under agile manufacturing mode, enterprises must have the capability of rapid reconfiguration, in which it is hard to avoid the conflicts of resources and interest and harmonizing is needed. Negotiation is the most effective way of harmonizing to solve the conflicts in this process. This paper is concerned with the research on the application of negotiation theory in Agile Manufacturing System. Main research work being carried out is as follows.
An Agent-based Framework of automated Negotiation has been constructed based on the theoretical discussion of the concept of Agent, the architecture of Multi-Agent System, communication language and related technology. After the advantages and disadvantages of some presently advanced theory such as negotiation on the Game Theory, heuristic negotiation, persuading negotiation and negotiation theory on machine learning is analyzed, The key technical problems to support automated negotiation, such as automatic execution technique of multi-task negotiation, the definition and formalization description of negotiation protocol, self-adapting of negotiation protocol and knowledge sharing problem in negotiation protocol and content ,etc. are studied.
An agile supply chain management system based on win-win negotiation is built up based on the analyzing of the relationship between competitions and co-operations among enterprises in agile manufacturing environment. The win-win negotiation model in the agile supply chain management system is studied mainly. After the problem of utility calculation and the problem of complete preferences information existing in conventional multi- issues negotiation model is systematically construed, the formula of utility computing is rationally modified, and the technique scheme which implements win-win negotiation under the condition of incomplete preferences information as well as self-adaptation negotiation strategy based on neural network learning technique are put forward, which are proved experimentally to be valid.
The mathematical model of reconfiguration algorithms based on negotiation has been advanced after the limitation not reflecting the dynamic character in Agile Manufacturing System in traditional reconfiguration algorithms based on integer programming is analyzed. A network resources integration scheme which can be realized by self-organization bidding based on the negotiation protocol of CNCP extension net is put forward. The integration scheme is optimized by using of genetic algorithm, and secondary biding is executed in order to obtain the feasibility of the optimization result. The experimental results indicate that: the method of system reconfiguration by negotiation is of scientific and suitable features, reflecting the dynamic character of agile manufacturing system.
With the systematic analysis of the co-operations relationship among enterprises in agile manufacturing environment, a control system model with the members taking the next machining task to catch up against the production schedule by economic compensation has been constructed, with its focus on the research of the one-to-more compensation negotiation model. The build-up of negotiation strategy under uniform restrained negotiation attributions is based on the idea of multiple-win using equal utility interpolation methods. The simulated experiment for classical time-cost negotiation problem is synthesized
Investigation has been carried out on Yellow page management mechanism of JADE platform and ACL communication language. Enterprise material purchasing negotiation system and agile manufacturing reconfiguration prototype system have been developed in agile manufacturing environment.
引文
[1] Raiffa H..The Art and Science of Negotiation[M]. Boston: Harvard University Press, 1982: 35-40.
[2] R.Davis, R.Smith. Frameworks for cooperation in distributed problem solving [J]. IEEE transactions on systems, man, and cybernetics, 1981, 11(1): 61-80.
[3] E.H.Durfee, V.Lesser. Negotiating task decomposition and allocation using partial global planning[J]. Distributed Artificial Intelligence, 1988, 2 (1): 229-243.
[4] N.R.Jennings, RFaratin, T.J.Norman, P.O'Bfien, B.Odgers, J.L.Alty. Implementing a Business Process ManagementSystem using ADEPT: A Real-World Case Study[J]. Journal of Applied Artificial Intelligence, 2000, 14(5): 421-463.
[5] Huhns M N, Stephens L M.. Multiagent System: A Modem Approach to Distributed Artifical Intelligence[M]. Boston: The MITPress, 1999: 545-600.
[6] Jennings R., Faratin P., Lomuscio A.R., et al. Automated negotiation: Prospects, methods and challenges[J], International Journal of Group Decision and Negotiation, 2001, 10(2): 199-215.
[7] Kraus S.. Automated Negotiation and decision making in Multi-agent Environments [J]. Mutli-agents systems and applications. Berlin: Springer-Verlag Press, 2001: 150-172.
[8] Kraus S.. Strategic negotiation in multi-agent environments[M]. Boston: The MIT Press, 2001: 120-125.
[9] Pillatt Fr, De Vit Ar, Da Silveira Jc, et al. Automating the Process of Negotiation in B2B Transactions through Software Agents [EB/OL]. http://din.funicruz.edu, 2006-08-15.
[10] J.P.Mueller. The design of Intelligent Agents:A Layered Approach[M]. Berlin: Springer Verlag KG, 1996: 1-227.
[11] Kersten.G.E.. Support for group decisions and negotiations[J]. An Overview, 1997, 12(3): 332-346.
[12] Teich J.E., H.Wallenius, J.Wallenius. Advances in negotiation science[J]. Transactions in Operational Research, 1994, 14(6): 55-94.
[13] A.Chavez, P.Maes. Kasbah: An agent maretplace for Buying and Selling Goods[R]. USA: The Proc. of The First International Conference on the Practial Application of Intelligent Agents and Multi-Agent Technology, 1996: 78.
[14] Sandholm T.. eMediator:A Next Generation Electronic Commerce Server [J]. Computational Intelligence, 2002, 18(4): 656-676.
[15] Tsvetovatyy M., Gini M.. Magma: An agent-based virtual market for electronic commerce[J]. Applied Artificial Intelligence, 1997, 11(6): 501-524.
[16] Sierra C., Faratin P, Jennings N.R.. A service_oriented negotiation mode Ibetween autonomous agents [R]. Sweden: The Proc. of the 8th European Workshop on Modeling Autonomous Agents in a MultiAgent World (MAAMAW_97), 1997: 17-35.
[17] 黄京华，马晖，赵纯均．面向电子商务的基本遗传算法的Agent谈判模型[J]．管理科学学报， 2002，5(2)：17-23．
[18] 张志超．敏捷制造的发展现状及其问题探讨[J]．机械研究与应用，1999，13(2)：3-4．
[19] 张洁．高亮．李培银．多Agent技术在先进制造中的应用[M]．北京：科学出版社，2004：166．
[20] Mark Klein, Peyman Faratin. Negotiation Algorithms for Collaborative Design Settings[R]. Portugal: The proceedings of the 10th ISPE International Conference on Concurrent Engineering Research and Applications (CERA-2003), 2003: 3-10.
[21] Sillence J. "Intelligent argumentation systems: requirements, models, research agenda, and applications," in Encyclopedia of Library and Information Science[M]. New York: Marcel Dekker, 1997: 176-217.
[22] Sycara, K., Navinchandra, D.. Integrating Case-Based Reasoning and Qualitative Reasoning in Engineering Design[J]. Artificial Intelligence in Engineering Design, 1989, 16(4): 216-234.
[23] 陈亮，金国栋，罗志伟．产品多学科协同设计的协商模型[J]．机械工程学报，2006，42(2)：175-181．
[24] 胡文斌．产品协同设计系统中交互式舣边协商问题研宄[J]．计算机集成制造，2006，12(3)：210-214．
[25] 孟秀丽，易红倪，中华，刘英．基于对策论的协同设计目标冲突协商方法研究[J]．中国机械工程，2004，24(3)：2190-2194．
[26] 年劲飞，黄道．供应链环境下基于Agent的协商决策[J]．华东理工大学学报，2004，30(6)：474-477．
[27] 高坚，张伟．多Agent系统中双边多指标自动协商的ACEA算法[J]．计算机研究与发展，2006，43(7)：1104-1108．
[28] Keesoo Kim, Boyd C Paulson,et al. Agent based electronic markets for project supply chain coordination[EB/OL].http://www.igec.umbc, edu/kbem/kinal/kim.pdf,2002-12-27.
[29] Sander vail def Putten. Automating Supply Chain Negotiations using Autonomous Agents: a Case Study in Transportation Logistics The Proc. of the 3th International Symposium on Electronic Commerce, 2006: 30-36.
[30] 张洁，刘世平，李培根．基于多Agent的车间重构模型[J]．中国机械工程，2000，11(4)：432-434．
[31] 李淑霞，单鸿波．基于敏捷制造单元的车间动态重构[J]．计算机集成制造系统，2007，14(3)：520-526．
[32] 凌兴宏，丁秋林，伍贝妮．基于协商的Multi-Agent生产计划与调度系统[J]．机械科学与技术，2004，19(2)：249-252．
[33] Butler J., Ohtsubo H.. architecture for distributed dynamic manufacturing scheduling[M]. Boston: The MITPress, 1992: 199-214.
[34] Shen W.. Norrie D.H.. An agent-based approach for dynamic manufacturing scheduling [R]. London, UK: The Proceedings of the 3rd International Conference on the Practical Applications of Agents and Multi-Agent Systems (PAAM-1998), 1998: 4-11.
[35] 史忠植．智能主体及其应用[M]．北京：科学出版社，2000：108-109．
[36] Jihad Reaidy, Pierre Massotte,Daniel Diep Comparise of negotiation protocols in dynamic agent-based manufacturing system[J]. Production Economics 99(2006): 117-130.
[37] Antonio Boccalatte,Andrea Gozzi,Massimo Paolucci,Valentina Queirolo A multi-Agent System for dynamic juest-in-time manufacturing production scheduling[J], IEEE internamtional conference on system, Man and cybernetics. 2004 P5548-5553.
[38] 严峰，王小平，曹立明．一种基于多Agent分布式协商框架的工程调度方法[J]．计算机应用与软件，2005，4(3)：23-45．
[39] 李英杰．模具虚拟企业制造项目协商规划与控制研究[D]．广东：广东工业大学，2006：60-63．
[40] D.T. Ndumu, H.S.Nwana. Research and development challenges for Agent-based system[J], IEE Proceedings on Software Engineering, 1997, 144(1): 2-10.
[41] Bradshaw J., Dutfield S., Benoit P., et al. Software Agents[M]. Boston: The MIT Press, 1997: 375-418.
[42] Wooldridge M., Jennings N.R., Kinny D. The gala methodology for agent-oriented analysis and design[J]. Autonomous Agents and Multi-Agent Systems, 2000, 3(3): 285-312.
[43] 谷雨，范菁，张天军 基于随机子空间法的多Agent分布式入侵检测[J]计算机工程 2007Vol．33 No．14 p121-123
[44] 李建强，范玉顺．Agent技术研究现状及其在企业技术中的应用[J]．计算机科学，2003，30(3)：71-74．
[45] Finin T., Labrou Y., Mayfield J.. KQML as an Agent Communication Language [R]. Gai thersburg, Maryland,USA: The Proceedings of the 3rd International Conference on Information and Knowledge Management (CIKM-1994), 1994: 1-22.
[46] Ya Yannis Labrou, Tim Finin. A Proposal for a new KQML Specification[EB/OL]. http://www.flacp.fujitsulabs.com/yannis/publications/tr9703.pdf, 1997-03-09/2007-06-30.
[47] ARPA Knowledge Sharing Initiative Specification of the KQML agent communication language[EB/OL], http://www.cs.umbc.edu/kqml/papers/kqml-spec.ps,, 1993-04-12/2007-06-30.
[48] 孙宪鹏，张宁．基于KQML语言的合同网协议模型及实现[J]．信息与控制，2000，29(5)：454-460．
[49] Burg B..Foundation for Intelligent Physical Agents[EB/OL].http://www.fipa./org/does/output/f-out-001111.2002-12-5/2007-06-30.
[50] 张德同，周明全，耿国华．FIPA规范：Agent系统的开放标准[J]．计算机科学，2002，29(5)：30-32．
[51] 张云勇，刘锦德．基于ACL的移动agent／智能agent互操作插件[J]．电子科技大学学报，2001，30(4)：407-413．
[52] Varoufakis, Y. General introduction: Game theory's quest for a single, unifying framework for the social sciences. In Varoufakis, Y. (ed.) Game Theory:Critical Concepts in the Social Sciences Volume 1. 2001. London: Routledge.
[53] Rosenschein J. S., Genesereth M.. Cooperation without communication: the problems of highly distributed working[R]. USA: The Proc. of the 5th National Conference on. Artificial. Intelligence(AAAI-1986), 1986: 51-57.
[54] Rosenschein J. S.. Rational Interaction:Cooperation Among Intelliagent Agents[D]. California: Stanford Univ., 1986: 50-52.
[55] Rosenschein J. S., Genesereth M. Deals among Resolution Via Negotiation[J]. The Ecology of Computation, 1988, 16(2): 117-132.
[56] Gmytrasiewicz P.J., Durfee E.H.. Elements of a Utilitarian Theory of Knowledge and Action [R]. Chambery, France: The Proceedings of the 12th International Joint Conference on Artificial Intelligence(IJCAI-1993), 1993: 396-403.
[57] Durfee E.H., Lee J., Gmytrasiewicz P. J. Overeager Reciprocal rationality and Mixed Strategy Equilibria[R]. USA: The Proceedings of the 12th International Workshop on Distributed Artificial Intelligence, 1993: 225-231.
[58] Gmytrasiewic P. J., Durfee E.H.. A Decision Theretic Approach to Coordinating Multiagent Interactions[R]. Sydney, Australia: The Proceedings of the 11th International Joint Conference on Artificial Intelligence (IJCAI-1991), 1991: 63-68.
[59] Ronen Brafman, Moshe Tennenholtz. A Near optimal Polynomial Time Algorithm for Learning in Certain Classes of Stochastic Games [J].Artificial Intelligence, 2000, 121 (1-2):31-47. [60] Jennings N.R., Faratin D., Johnson M.J., et al. Agent-Based business process management[J]. Cooperative Information Systems, 1996, 5(2,3): 105-130.
[61] Sierra C., Faratin D., Jermings N.R.. A service-oriented negotiation model between autonomous agents[R]. Ronneby, Sweden: The Proceedings of the 8th European Workshop on Modeling Autonomous Agents in a Multi-agent World (MAAMAW-1997), 1997: 17-35.
[62] N.R.Jennings, P.Faratin, A.R.Lomuscio, S.Parsons, C.Sierra, M.Wooldridge. Automated negotiation: prospects, methods and challenge[J]. Group Decision and negotiation, 2001, 10(2): 199-215.
[63] N.R.Jennings, S.Parsons, C.sierra, P.Faratin. Automated negotiation[R]. Manchester, UK: The proceedings of 5th International conference on Practical Application of Intelligent Agents and MultiAgent System(PAAM-2000), 2000: 15-20.
[64] S.Kraus, J.Wilkenfeld, G.Zlotkin. Multi-agent negotiation under time constraints[J] Artificial Intelligence, 1995, 75(2): 297-345.
[65] S.Kraus. Beliefs, time and incomplete information in multiple encounter negotiations among autonomous agents[J]. Mathematics and Artificial Intelligence, 1997, 20(1-4): 111-159.
[66] 陆汝鈐 知识科学与计算科学[M]清华大学出版社，2002，3：103-103．
[67] Kowalczyk, R., Van Anh Bui. FeNAs: a fuzzy e-negotiation agents system[R]. New York City, Crowne Plaza Manhattan,USA: The Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr-2000), 2000:26-29.
[68] Sycara K., Roth S., SadehN., Fox M.. Distributed constrained heuristic search[J]. IEEE Transaction on System, Man and Cybernetics, 1991, 21(6): 1446-1461.
[69] S. D. Ramchurn, N. R. Jennings, C. Sierra. Persuasive negotiation for autonomous agents: A rhetorical approach[R]. Acapulco, Mexico: The Proceedings of the 17th International Joint Conference on Artificial Intelligence(IJCAI-2003) Workshop on the Computational Models of Natural Argument, 2003: 9-18.
[70] L.Amgoud, N.Maudet, S.Parsons. Modelling dialogues using argumentation[R]. Boston, USA: In the proceedings of the 4th Int Conference on Multi-Agent System, 2000: 2-16.
[71] Jelle Van Veenen, Henry Prakken. A verifiable protocol for arguing about rejections in negotiation[R]. Utrecht, The Netherlands: The Proceedings of the 4th international joint conference on Autonomous Agents and Multiagent systems (AAMAS-2005), 2005: 1165-1166.
[72] Vreeswijk. Abstract argumentation systems[J]. Artificial Intelligence, 1997, 90(1-2): 225-279.
[73] 杨佩，高阳，陈兆乾．一种劝说式多Agent多议题协商方法[J]．计算机研究与发展，2006，7(2)：1149-1154．
[74] Sycara Cyranski K. Arguments of persuasion in labor mediation[R]. Los Angeles, California, USA: In The Proceedings of the 9th International Joint Conference on Artificial Intelligence (IJCAI-1985), 1985:294-296.
[75] Sycarra K.. machine learning for intelligent support of conflict resolution[J]. Decision Support systems, 1993, 10(2): 121-136.
[76] Zeng D., Sycara K.. Bayesian learning in Negotiation[J]. Human-Computer Systems, 1998, 48(3): 125-141,199.
[77] Gerald Tesauro. Efficient Search Techniques for Multi_Attribute Bilateral Negotiation Strategies[R]. USA: The Proceedings of the 3rd International Symposium on Electronic Commerce(ISEC-2002), 2002: 23-24.
[78] Zeng D., Sycara K.. Learning Opponent's Eagerness with Bayesian Updating Rule[J]. Human Computer Systems, 1998, 48(5): 125-141.
[79] 王娟，柴玉梅 基于多议题协商的贝叶斯学习[J]．计算机技术与发展，2006．2001．16 No．2：154-156．
[80] Watkins C. J. C. H., Dayan P.. Technical Note: Q-Learning[J]. Machine Learning, 1992, 8(2): 279-292.
[81] Tesauro G., Kephart G.O.. Pricing in Agent Economies Using Multiagent Q-learning[J]. Autonomous Agents and Multi-agent Systems, 2002, 5(3): 289-304.
[82] Sridharan M., Tesauro G.. Multi-agent Q-learning and Regression Trees for Automated Pricing Decisions[R]. Stanford, California,USA: The Proc. of the 17th International Conf. on Machine Learning (ICML-2000), 2000: 927-934.
[83] 王立春．高阳．AODE中基于强化学习的Agent协商模型[J]．南京大学学报，2001，37(2)：135-141．
[84] 张化祥，黄上腾．基于增强学习的代理谈判模型[J]．计算机工程．2004，30(10)：137-139．
[85] Oliver J.R.. A Machine Learning Approach to Automated Negotiation and Prospects for Electronic Commerce[J]. Management Information Systems, 1997, 13(3): 83-112.
[86] Oliver J.R.. On Artificial agents for Negotiation in Electronic Commerce[R]. Hawaii,USA: The Proceedings of the 29th Annual Hawaii International Conference on System Sciences, 1996: 23-46.
[87] Katy Borner.Structural Similarity as Guidance in Case-based Design[R]. Kaiserslautem,Germany: The First European Workshop on Topics in Case-based Reasoning. 1993: 14-19.
[88] 韩军，车文刚．CBR—一种新型的人工智能推理方法[J]．昆明理工大学学报，2003，28(1)：88-91．
[89] Fu-ren Lin, Kuang-yi Chang. A Multiagent Framework for Automated Online Bargaining [J]. IEEE Intelligent System, 2001, 8 (4): 41-47.
[90] 杨玲丽，刘涛．基于XML的智能化电子商务模型[J]．中国水运(理论版)，2006，4(1)：61-62．
[91] 丘威，张立臣．XML DTD规范化处理应用研究[J]．计算机科学，2006，33(3)：63-67．
[92] 宓永迪，夏勇．资源描述框架RDF的应用[J]．大学图书馆学报，2001，12(2)：24-26．
[93] 林春梅，金鑫，何跃．基RDF构建语义化本体模型[J]．计算机应用与软件，2002，16(6)：32-34．
[94] 谢天保，张璟．智能电子商务工作流结构与标准化问题研究[J]．计算机工程，2003，29(2)：11-24．
[95] 谢天保，张璟．基于工作流管理的智能制造系统[J]．计算机工程，2005，31(2)：47-49．
[96] KSL. Knowledge Interchange Format, Version0.3, Reference Manual. Knowledge Systems Laboratory[S]. Stanford, Califomia,USA: Stanford University Press, 1992.
[97] Karp P. D., Chaudhri V. K., Thomere J.. XOL:An XML-Based Ontology Exchange Language[EB/OL]. http://www, ai.sri.com/pkarp/xol/xol.html, 1999-05-06/2007-06-30.
[98] Horrocks I., Patel-Schneider P. F., Harmelen F.. Reviewing the design of DAML+OIL:an ontology language for the semantic web[R]. USA: The Proceedings of the 16th National Conference on Artificial Intelligence(AAAI-2002). 2002: 24.
[99] M. Hori, J. Euzenat, P. F. Patel-Schneider. OWL Web Ontology Language XML Presentation Syntax. W3C Note 11 June 2003[EB/OL]. http://www.w3.org/TR/2003/NOTE-owl xmlsyntax-20030611/#sec-root, 2003-06-11/2007-06-30.
[100] McGuinness D. L., Harmelen F. V.. OWL Web ontology language overview[EB/OL]. http://www.w3.org/TR/2004/REC-owl-features-20040210/, 2004-08-09/2007-06-30.
[101] Ralf Neubert, Tobias Teich . Automated negotiation of supply contracts for flexible production networks[J]. Production Economics, 2004, 89(2): 175-187.
[102] AMR Research. The report on Supply Chain Management[R]. USA: AMR Research, 1998: 5.
[103] M.Barbuceanu, M.S.Fox. The Information Agent: An Infrastructure Agent Supporting Collaborative Enterprise Architectures[R]. Morgantown, West Virginia, USA: The Proceedings of the 3rd workshop on Enabling Technologies: Infrastructure for Collaborative Enterprise, 1996: 81-96.
[104] Sadeh N. M., Hildum D. W., Kjenstad D., Tseng A.. MASCOT: an agent-based architecture for dynamic supply chain creation and coordination in the internet economy[J]. Production Planning and Control, 1996, 12(3): 55-60.
[105] Chun Wang, Weiming Shen. An adaptive Negotiation Framework for Agent Based Dynamic Manufacturing Scheduling[J]. IEEE Intelligent System, 2002, 45(1-2): 88-94.
[106] Gmytrasiewicz P.J., Dufee E.H.. Elements of a Utilitarian Theory of Knowledge and Ation[R]. Chambery, France: The Proceedings of the 12th International Joint Conference on Artificial Intelligence(IJCAI-1993), 1993: 396-403.
[107] George F．Luger著，史忠植等译．人工智能-复杂问题求解的结构和策略(第四版)[M]．北京：机械工业出版社，2004：101-109．
[108] 伍乃骐，毛宁，钱燕鸣．敏捷制造下车间重构中的制造资源选择[J]．信息与控制，1999，28(2)：416-422．
[109] 石柯，高亮，张洁，李培根．敏捷制造单元动态重构研究[J]．机械科学与技术，2001，20(5)：654-656．
[110] 刘海龙，吴铁军．基于合同网的多agent任务分配分布式优化算法[J]．浙江大学学报，2004，4(2)：471-475．
[111] Schillo M., Kray C., Fischer K.. The eager bidder problem: a fundamental problem of DAI and selected solutions[R]. Bologna, Italy:The Proceedings of the 1st International Joint Conference on Autonomous Agents and Multiagent Systems(AAMAS-2002), 2002: 599-606.
[112] 姚倡锋，张定华，彭文莉．基于遗传算法的网络化制造单元选择问题研究[J]．计算机集成制造COMS，2004，12(3)：1555-1559．
[113] 曾晓青．基于多智能体的虚拟企业协同生产规划研究[D]．湖南：中南大学，2003：87．
[114] Bellifemine F., Caire G, TRUCCO T., et al. JADE Administrator's Guide, JADE Programmer's Guide [EB/OL]. http://jade.tilab.com/doc/index.html
[2] R.Davis, R.Smith. Frameworks for cooperation in distributed problem solving [J]. IEEE transactions on systems, man, and cybernetics, 1981, 11(1): 61-80.
[3] E.H.Durfee, V.Lesser. Negotiating task decomposition and allocation using partial global planning[J]. Distributed Artificial Intelligence, 1988, 2 (1): 229-243.
[4] N.R.Jennings, RFaratin, T.J.Norman, P.O'Bfien, B.Odgers, J.L.Alty. Implementing a Business Process ManagementSystem using ADEPT: A Real-World Case Study[J]. Journal of Applied Artificial Intelligence, 2000, 14(5): 421-463.
[5] Huhns M N, Stephens L M.. Multiagent System: A Modem Approach to Distributed Artifical Intelligence[M]. Boston: The MITPress, 1999: 545-600.
[6] Jennings R., Faratin P., Lomuscio A.R., et al. Automated negotiation: Prospects, methods and challenges[J], International Journal of Group Decision and Negotiation, 2001, 10(2): 199-215.
[7] Kraus S.. Automated Negotiation and decision making in Multi-agent Environments [J]. Mutli-agents systems and applications. Berlin: Springer-Verlag Press, 2001: 150-172.
[8] Kraus S.. Strategic negotiation in multi-agent environments[M]. Boston: The MIT Press, 2001: 120-125.
[9] Pillatt Fr, De Vit Ar, Da Silveira Jc, et al. Automating the Process of Negotiation in B2B Transactions through Software Agents [EB/OL]. http://din.funicruz.edu, 2006-08-15.
[10] J.P.Mueller. The design of Intelligent Agents:A Layered Approach[M]. Berlin: Springer Verlag KG, 1996: 1-227.
[11] Kersten.G.E.. Support for group decisions and negotiations[J]. An Overview, 1997, 12(3): 332-346.
[12] Teich J.E., H.Wallenius, J.Wallenius. Advances in negotiation science[J]. Transactions in Operational Research, 1994, 14(6): 55-94.
[13] A.Chavez, P.Maes. Kasbah: An agent maretplace for Buying and Selling Goods[R]. USA: The Proc. of The First International Conference on the Practial Application of Intelligent Agents and Multi-Agent Technology, 1996: 78.
[14] Sandholm T.. eMediator:A Next Generation Electronic Commerce Server [J]. Computational Intelligence, 2002, 18(4): 656-676.
[15] Tsvetovatyy M., Gini M.. Magma: An agent-based virtual market for electronic commerce[J]. Applied Artificial Intelligence, 1997, 11(6): 501-524.
[16] Sierra C., Faratin P, Jennings N.R.. A service_oriented negotiation mode Ibetween autonomous agents [R]. Sweden: The Proc. of the 8th European Workshop on Modeling Autonomous Agents in a MultiAgent World (MAAMAW_97), 1997: 17-35.
[17] 黄京华，马晖，赵纯均．面向电子商务的基本遗传算法的Agent谈判模型[J]．管理科学学报， 2002，5(2)：17-23．
[18] 张志超．敏捷制造的发展现状及其问题探讨[J]．机械研究与应用，1999，13(2)：3-4．
[19] 张洁．高亮．李培银．多Agent技术在先进制造中的应用[M]．北京：科学出版社，2004：166．
[20] Mark Klein, Peyman Faratin. Negotiation Algorithms for Collaborative Design Settings[R]. Portugal: The proceedings of the 10th ISPE International Conference on Concurrent Engineering Research and Applications (CERA-2003), 2003: 3-10.
[21] Sillence J. "Intelligent argumentation systems: requirements, models, research agenda, and applications," in Encyclopedia of Library and Information Science[M]. New York: Marcel Dekker, 1997: 176-217.
[22] Sycara, K., Navinchandra, D.. Integrating Case-Based Reasoning and Qualitative Reasoning in Engineering Design[J]. Artificial Intelligence in Engineering Design, 1989, 16(4): 216-234.
[23] 陈亮，金国栋，罗志伟．产品多学科协同设计的协商模型[J]．机械工程学报，2006，42(2)：175-181．
[24] 胡文斌．产品协同设计系统中交互式舣边协商问题研宄[J]．计算机集成制造，2006，12(3)：210-214．
[25] 孟秀丽，易红倪，中华，刘英．基于对策论的协同设计目标冲突协商方法研究[J]．中国机械工程，2004，24(3)：2190-2194．
[26] 年劲飞，黄道．供应链环境下基于Agent的协商决策[J]．华东理工大学学报，2004，30(6)：474-477．
[27] 高坚，张伟．多Agent系统中双边多指标自动协商的ACEA算法[J]．计算机研究与发展，2006，43(7)：1104-1108．
[28] Keesoo Kim, Boyd C Paulson,et al. Agent based electronic markets for project supply chain coordination[EB/OL].http://www.igec.umbc, edu/kbem/kinal/kim.pdf,2002-12-27.
[29] Sander vail def Putten. Automating Supply Chain Negotiations using Autonomous Agents: a Case Study in Transportation Logistics The Proc. of the 3th International Symposium on Electronic Commerce, 2006: 30-36.
[30] 张洁，刘世平，李培根．基于多Agent的车间重构模型[J]．中国机械工程，2000，11(4)：432-434．
[31] 李淑霞，单鸿波．基于敏捷制造单元的车间动态重构[J]．计算机集成制造系统，2007，14(3)：520-526．
[32] 凌兴宏，丁秋林，伍贝妮．基于协商的Multi-Agent生产计划与调度系统[J]．机械科学与技术，2004，19(2)：249-252．
[33] Butler J., Ohtsubo H.. architecture for distributed dynamic manufacturing scheduling[M]. Boston: The MITPress, 1992: 199-214.
[34] Shen W.. Norrie D.H.. An agent-based approach for dynamic manufacturing scheduling [R]. London, UK: The Proceedings of the 3rd International Conference on the Practical Applications of Agents and Multi-Agent Systems (PAAM-1998), 1998: 4-11.
[35] 史忠植．智能主体及其应用[M]．北京：科学出版社，2000：108-109．
[36] Jihad Reaidy, Pierre Massotte,Daniel Diep Comparise of negotiation protocols in dynamic agent-based manufacturing system[J]. Production Economics 99(2006): 117-130.
[37] Antonio Boccalatte,Andrea Gozzi,Massimo Paolucci,Valentina Queirolo A multi-Agent System for dynamic juest-in-time manufacturing production scheduling[J], IEEE internamtional conference on system, Man and cybernetics. 2004 P5548-5553.
[38] 严峰，王小平，曹立明．一种基于多Agent分布式协商框架的工程调度方法[J]．计算机应用与软件，2005，4(3)：23-45．
[39] 李英杰．模具虚拟企业制造项目协商规划与控制研究[D]．广东：广东工业大学，2006：60-63．
[40] D.T. Ndumu, H.S.Nwana. Research and development challenges for Agent-based system[J], IEE Proceedings on Software Engineering, 1997, 144(1): 2-10.
[41] Bradshaw J., Dutfield S., Benoit P., et al. Software Agents[M]. Boston: The MIT Press, 1997: 375-418.
[42] Wooldridge M., Jennings N.R., Kinny D. The gala methodology for agent-oriented analysis and design[J]. Autonomous Agents and Multi-Agent Systems, 2000, 3(3): 285-312.
[43] 谷雨，范菁，张天军 基于随机子空间法的多Agent分布式入侵检测[J]计算机工程 2007Vol．33 No．14 p121-123
[44] 李建强，范玉顺．Agent技术研究现状及其在企业技术中的应用[J]．计算机科学，2003，30(3)：71-74．
[45] Finin T., Labrou Y., Mayfield J.. KQML as an Agent Communication Language [R]. Gai thersburg, Maryland,USA: The Proceedings of the 3rd International Conference on Information and Knowledge Management (CIKM-1994), 1994: 1-22.
[46] Ya Yannis Labrou, Tim Finin. A Proposal for a new KQML Specification[EB/OL]. http://www.flacp.fujitsulabs.com/yannis/publications/tr9703.pdf, 1997-03-09/2007-06-30.
[47] ARPA Knowledge Sharing Initiative Specification of the KQML agent communication language[EB/OL], http://www.cs.umbc.edu/kqml/papers/kqml-spec.ps,, 1993-04-12/2007-06-30.
[48] 孙宪鹏，张宁．基于KQML语言的合同网协议模型及实现[J]．信息与控制，2000，29(5)：454-460．
[49] Burg B..Foundation for Intelligent Physical Agents[EB/OL].http://www.fipa./org/does/output/f-out-001111.2002-12-5/2007-06-30.
[50] 张德同，周明全，耿国华．FIPA规范：Agent系统的开放标准[J]．计算机科学，2002，29(5)：30-32．
[51] 张云勇，刘锦德．基于ACL的移动agent／智能agent互操作插件[J]．电子科技大学学报，2001，30(4)：407-413．
[52] Varoufakis, Y. General introduction: Game theory's quest for a single, unifying framework for the social sciences. In Varoufakis, Y. (ed.) Game Theory:Critical Concepts in the Social Sciences Volume 1. 2001. London: Routledge.
[53] Rosenschein J. S., Genesereth M.. Cooperation without communication: the problems of highly distributed working[R]. USA: The Proc. of the 5th National Conference on. Artificial. Intelligence(AAAI-1986), 1986: 51-57.
[54] Rosenschein J. S.. Rational Interaction:Cooperation Among Intelliagent Agents[D]. California: Stanford Univ., 1986: 50-52.
[55] Rosenschein J. S., Genesereth M. Deals among Resolution Via Negotiation[J]. The Ecology of Computation, 1988, 16(2): 117-132.
[56] Gmytrasiewicz P.J., Durfee E.H.. Elements of a Utilitarian Theory of Knowledge and Action [R]. Chambery, France: The Proceedings of the 12th International Joint Conference on Artificial Intelligence(IJCAI-1993), 1993: 396-403.
[57] Durfee E.H., Lee J., Gmytrasiewicz P. J. Overeager Reciprocal rationality and Mixed Strategy Equilibria[R]. USA: The Proceedings of the 12th International Workshop on Distributed Artificial Intelligence, 1993: 225-231.
[58] Gmytrasiewic P. J., Durfee E.H.. A Decision Theretic Approach to Coordinating Multiagent Interactions[R]. Sydney, Australia: The Proceedings of the 11th International Joint Conference on Artificial Intelligence (IJCAI-1991), 1991: 63-68.
[59] Ronen Brafman, Moshe Tennenholtz. A Near optimal Polynomial Time Algorithm for Learning in Certain Classes of Stochastic Games [J].Artificial Intelligence, 2000, 121 (1-2):31-47. [60] Jennings N.R., Faratin D., Johnson M.J., et al. Agent-Based business process management[J]. Cooperative Information Systems, 1996, 5(2,3): 105-130.
[61] Sierra C., Faratin D., Jermings N.R.. A service-oriented negotiation model between autonomous agents[R]. Ronneby, Sweden: The Proceedings of the 8th European Workshop on Modeling Autonomous Agents in a Multi-agent World (MAAMAW-1997), 1997: 17-35.
[62] N.R.Jennings, P.Faratin, A.R.Lomuscio, S.Parsons, C.Sierra, M.Wooldridge. Automated negotiation: prospects, methods and challenge[J]. Group Decision and negotiation, 2001, 10(2): 199-215.
[63] N.R.Jennings, S.Parsons, C.sierra, P.Faratin. Automated negotiation[R]. Manchester, UK: The proceedings of 5th International conference on Practical Application of Intelligent Agents and MultiAgent System(PAAM-2000), 2000: 15-20.
[64] S.Kraus, J.Wilkenfeld, G.Zlotkin. Multi-agent negotiation under time constraints[J] Artificial Intelligence, 1995, 75(2): 297-345.
[65] S.Kraus. Beliefs, time and incomplete information in multiple encounter negotiations among autonomous agents[J]. Mathematics and Artificial Intelligence, 1997, 20(1-4): 111-159.
[66] 陆汝鈐 知识科学与计算科学[M]清华大学出版社，2002，3：103-103．
[67] Kowalczyk, R., Van Anh Bui. FeNAs: a fuzzy e-negotiation agents system[R]. New York City, Crowne Plaza Manhattan,USA: The Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr-2000), 2000:26-29.
[68] Sycara K., Roth S., SadehN., Fox M.. Distributed constrained heuristic search[J]. IEEE Transaction on System, Man and Cybernetics, 1991, 21(6): 1446-1461.
[69] S. D. Ramchurn, N. R. Jennings, C. Sierra. Persuasive negotiation for autonomous agents: A rhetorical approach[R]. Acapulco, Mexico: The Proceedings of the 17th International Joint Conference on Artificial Intelligence(IJCAI-2003) Workshop on the Computational Models of Natural Argument, 2003: 9-18.
[70] L.Amgoud, N.Maudet, S.Parsons. Modelling dialogues using argumentation[R]. Boston, USA: In the proceedings of the 4th Int Conference on Multi-Agent System, 2000: 2-16.
[71] Jelle Van Veenen, Henry Prakken. A verifiable protocol for arguing about rejections in negotiation[R]. Utrecht, The Netherlands: The Proceedings of the 4th international joint conference on Autonomous Agents and Multiagent systems (AAMAS-2005), 2005: 1165-1166.
[72] Vreeswijk. Abstract argumentation systems[J]. Artificial Intelligence, 1997, 90(1-2): 225-279.
[73] 杨佩，高阳，陈兆乾．一种劝说式多Agent多议题协商方法[J]．计算机研究与发展，2006，7(2)：1149-1154．
[74] Sycara Cyranski K. Arguments of persuasion in labor mediation[R]. Los Angeles, California, USA: In The Proceedings of the 9th International Joint Conference on Artificial Intelligence (IJCAI-1985), 1985:294-296.
[75] Sycarra K.. machine learning for intelligent support of conflict resolution[J]. Decision Support systems, 1993, 10(2): 121-136.
[76] Zeng D., Sycara K.. Bayesian learning in Negotiation[J]. Human-Computer Systems, 1998, 48(3): 125-141,199.
[77] Gerald Tesauro. Efficient Search Techniques for Multi_Attribute Bilateral Negotiation Strategies[R]. USA: The Proceedings of the 3rd International Symposium on Electronic Commerce(ISEC-2002), 2002: 23-24.
[78] Zeng D., Sycara K.. Learning Opponent's Eagerness with Bayesian Updating Rule[J]. Human Computer Systems, 1998, 48(5): 125-141.
[79] 王娟，柴玉梅 基于多议题协商的贝叶斯学习[J]．计算机技术与发展，2006．2001．16 No．2：154-156．
[80] Watkins C. J. C. H., Dayan P.. Technical Note: Q-Learning[J]. Machine Learning, 1992, 8(2): 279-292.
[81] Tesauro G., Kephart G.O.. Pricing in Agent Economies Using Multiagent Q-learning[J]. Autonomous Agents and Multi-agent Systems, 2002, 5(3): 289-304.
[82] Sridharan M., Tesauro G.. Multi-agent Q-learning and Regression Trees for Automated Pricing Decisions[R]. Stanford, California,USA: The Proc. of the 17th International Conf. on Machine Learning (ICML-2000), 2000: 927-934.
[83] 王立春．高阳．AODE中基于强化学习的Agent协商模型[J]．南京大学学报，2001，37(2)：135-141．
[84] 张化祥，黄上腾．基于增强学习的代理谈判模型[J]．计算机工程．2004，30(10)：137-139．
[85] Oliver J.R.. A Machine Learning Approach to Automated Negotiation and Prospects for Electronic Commerce[J]. Management Information Systems, 1997, 13(3): 83-112.
[86] Oliver J.R.. On Artificial agents for Negotiation in Electronic Commerce[R]. Hawaii,USA: The Proceedings of the 29th Annual Hawaii International Conference on System Sciences, 1996: 23-46.
[87] Katy Borner.Structural Similarity as Guidance in Case-based Design[R]. Kaiserslautem,Germany: The First European Workshop on Topics in Case-based Reasoning. 1993: 14-19.
[88] 韩军，车文刚．CBR—一种新型的人工智能推理方法[J]．昆明理工大学学报，2003，28(1)：88-91．
[89] Fu-ren Lin, Kuang-yi Chang. A Multiagent Framework for Automated Online Bargaining [J]. IEEE Intelligent System, 2001, 8 (4): 41-47.
[90] 杨玲丽，刘涛．基于XML的智能化电子商务模型[J]．中国水运(理论版)，2006，4(1)：61-62．
[91] 丘威，张立臣．XML DTD规范化处理应用研究[J]．计算机科学，2006，33(3)：63-67．
[92] 宓永迪，夏勇．资源描述框架RDF的应用[J]．大学图书馆学报，2001，12(2)：24-26．
[93] 林春梅，金鑫，何跃．基RDF构建语义化本体模型[J]．计算机应用与软件，2002，16(6)：32-34．
[94] 谢天保，张璟．智能电子商务工作流结构与标准化问题研究[J]．计算机工程，2003，29(2)：11-24．
[95] 谢天保，张璟．基于工作流管理的智能制造系统[J]．计算机工程，2005，31(2)：47-49．
[96] KSL. Knowledge Interchange Format, Version0.3, Reference Manual. Knowledge Systems Laboratory[S]. Stanford, Califomia,USA: Stanford University Press, 1992.
[97] Karp P. D., Chaudhri V. K., Thomere J.. XOL:An XML-Based Ontology Exchange Language[EB/OL]. http://www, ai.sri.com/pkarp/xol/xol.html, 1999-05-06/2007-06-30.
[98] Horrocks I., Patel-Schneider P. F., Harmelen F.. Reviewing the design of DAML+OIL:an ontology language for the semantic web[R]. USA: The Proceedings of the 16th National Conference on Artificial Intelligence(AAAI-2002). 2002: 24.
[99] M. Hori, J. Euzenat, P. F. Patel-Schneider. OWL Web Ontology Language XML Presentation Syntax. W3C Note 11 June 2003[EB/OL]. http://www.w3.org/TR/2003/NOTE-owl xmlsyntax-20030611/#sec-root, 2003-06-11/2007-06-30.
[100] McGuinness D. L., Harmelen F. V.. OWL Web ontology language overview[EB/OL]. http://www.w3.org/TR/2004/REC-owl-features-20040210/, 2004-08-09/2007-06-30.
[101] Ralf Neubert, Tobias Teich . Automated negotiation of supply contracts for flexible production networks[J]. Production Economics, 2004, 89(2): 175-187.
[102] AMR Research. The report on Supply Chain Management[R]. USA: AMR Research, 1998: 5.
[103] M.Barbuceanu, M.S.Fox. The Information Agent: An Infrastructure Agent Supporting Collaborative Enterprise Architectures[R]. Morgantown, West Virginia, USA: The Proceedings of the 3rd workshop on Enabling Technologies: Infrastructure for Collaborative Enterprise, 1996: 81-96.
[104] Sadeh N. M., Hildum D. W., Kjenstad D., Tseng A.. MASCOT: an agent-based architecture for dynamic supply chain creation and coordination in the internet economy[J]. Production Planning and Control, 1996, 12(3): 55-60.
[105] Chun Wang, Weiming Shen. An adaptive Negotiation Framework for Agent Based Dynamic Manufacturing Scheduling[J]. IEEE Intelligent System, 2002, 45(1-2): 88-94.
[106] Gmytrasiewicz P.J., Dufee E.H.. Elements of a Utilitarian Theory of Knowledge and Ation[R]. Chambery, France: The Proceedings of the 12th International Joint Conference on Artificial Intelligence(IJCAI-1993), 1993: 396-403.
[107] George F．Luger著，史忠植等译．人工智能-复杂问题求解的结构和策略(第四版)[M]．北京：机械工业出版社，2004：101-109．
[108] 伍乃骐，毛宁，钱燕鸣．敏捷制造下车间重构中的制造资源选择[J]．信息与控制，1999，28(2)：416-422．
[109] 石柯，高亮，张洁，李培根．敏捷制造单元动态重构研究[J]．机械科学与技术，2001，20(5)：654-656．
[110] 刘海龙，吴铁军．基于合同网的多agent任务分配分布式优化算法[J]．浙江大学学报，2004，4(2)：471-475．
[111] Schillo M., Kray C., Fischer K.. The eager bidder problem: a fundamental problem of DAI and selected solutions[R]. Bologna, Italy:The Proceedings of the 1st International Joint Conference on Autonomous Agents and Multiagent Systems(AAMAS-2002), 2002: 599-606.
[112] 姚倡锋，张定华，彭文莉．基于遗传算法的网络化制造单元选择问题研究[J]．计算机集成制造COMS，2004，12(3)：1555-1559．
[113] 曾晓青．基于多智能体的虚拟企业协同生产规划研究[D]．湖南：中南大学，2003：87．
[114] Bellifemine F., Caire G, TRUCCO T., et al. JADE Administrator's Guide, JADE Programmer's Guide [EB/OL]. http://jade.tilab.com/doc/index.html