skip to main content
10.1145/1089551.1089604acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicecConference Proceedingsconference-collections
Article

Adaptive negotiation agents for e-business

Published: 15 August 2005 Publication History

Abstract

Negotiation has been identified as one of the key steps in Business-to-Business (B2B) transaction models. However, developing effective and efficient negotiation mechanisms for e-Business is quite challenging since negotiations in such a context are characterized by combinatorial complex negotiation spaces, tough deadlines, incomplete information about the opponents, and volatile negotiator preferences. Classical negotiation models are not able to offer a satisfactory solution to address all these issues. This paper illustrates our adaptive negotiation agents which are underpinned by a robust evolutionary learning mechanism to deal with complex and dynamic negotiation situations often encountered in e-Business applications. Our experimental results show that the proposed evolutionary negotiation agents outperform a theoretically optimal negotiation mechanism which guarantees Pareto optimal. Our research work opens the door to the development of practical negotiation systems for e-Business.

References

[1]
Mihai Barbuceanu and Wai-Kau Lo. Multi-attribute utility theoretic negotiation for electronic commerce. In Frank Dignum and Ulises Cort'es, editors, Agent-Mediated Electronic Commerce III --- Current Issues in Agent Based Electronic Commerce Systems, number 2003 in Lecture Notes in Artifical Intelligence, pages 15--30. Springer-Verlag: Heidelberg, Germany, 2001.]]
[2]
D. Box. Simple Object Access Protocol (SOAP) 1.1, May 2000. Available from http: //www.w3.org/TR/SOAP/.]]
[3]
N. Davies, D. Fensel, and M. Richardson. The future of web services. BT Technology Journal, 22(1):118--130, 2004.]]
[4]
R. Duda and P. Hart. Pattern Classification and Scene Analysis. John Wiley & Sons, New York, New York, 1973.]]
[5]
P. Faratin, C. Sierra, and N. R. Jennings. Negotiation decision functions for autonomous agents. Journal of Robotics and Autonomous Systems, 24(3-4):159--182, 1998.]]
[6]
P. Faratin, C. Sierra, and N. R. Jennings. Using similarity criteria to make issue trade-offs in automated negotiations. Artificial Intelligence, 142(2):205--237, 2002.]]
[7]
S. Fatima, M. Wooldridge, and N. R. Jennings. Comparing Equilibria for Game-Theoretic and Evolutionary Bargaining Models. In Proceedings of the International Workshop on Agent-Mediated Electronic Commerce V, pages 70--77, Melbourne, Australia, 2003.]]
[8]
S. Fatima, M. Wooldridge, and N. R. Jennings. An agenda based framework for multi-issues negotiation. Artificial Intelligence, 152(1):1--45, 2004.]]
[9]
D. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, Massachusetts, 1989.]]
[10]
R. Guttman, A. Moukas, and P. Maes. Agent-mediated electronic commerce: A survey. Knowledge Engineering Review, 13(2):147--159, June 1998.]]
[11]
J. Harsanyi and R. Selten. A generalised nash solution for two-person bargaining games with incomplete information. Management Sciences, 18(5):80--106, 1972.]]
[12]
M. He, N. R. Jennings, and H. Leung. On agent-mediated electronic commerce. IEEE Trans. on Knowledge and Data Engineering, 15(4):985--1003, 2003.]]
[13]
N. R. Jennings, P. Faratin, A. R. Lomuscio, S. Parsons, C. Sierra, and M. Wooldridge. Automated negotiation: prospects, methods and challenges. Journal of Group Decision and Negotiation, 10(2):199--215, 2001.]]
[14]
R. Keeney and H. Raiffa. Decisions with Multiple Objectives: Preferences and Value Tradeoffs. Cambridge University Press, Cambridge, UK, 1993.]]
[15]
Sarit Kraus, Katia Sycara, and Amir Evenchik. Reaching agreements through argumentation: A logical model and implementation. Artificial Intelligence, 104(1--2):1--69, 1998.]]
[16]
R. Krovi, A. Graesser, and W. Pracht. Agent behaviors in virtual negotiation environments. IEEE Transactions on Systems, Man, and Cybernetics, 29(1):15--25, February 1999.]]
[17]
R. Y. K. Lau and S. Y. Chan. Towards Belief Revision Logic-Based Adaptive and Persuasive Negotiation Agents. In J. G. Carbonell and J. Siekmann, editors, Proceedings of the 8th Pacific Rim International Conference on Artificial Intelligence (PRICAI'04), volume 3157 of Lecture Notes in Artificial Intelligence, pages 605--614, Auckland, New Zealand, August 9--13 2004. Springer.]]
[18]
R. Y. K. Lau, B. Essam, S. Y. Chan and Z. Huang. Belief Revision for Adaptive Negotiation Agents. In Proceedings of the 3rd IEEE/WIC International Conference on Intelligent Agent Technology, pages 196--202, Halifax, Canada, October 13--17 2003. IEEE Computer Society.]]
[19]
R. Y. K. Lau, M. Tang, and O. Wong. Towards Genetically Optimised Responsive Negotiation Agents. In Proceedings of the 4th IEEE/WIC International Conference on Intelligent Agent Technology, pages 295--301, Beijing, China, September 20--24 2004. IEEE Computer Society.]]
[20]
A. R. Lomuscio and N. R. Jennings. A classification scheme for negotiation in electronic commerce. Journal of Group Decision and Negotiation, 12(1):31--56, 2003.]]
[21]
N. Matos, C. Sierra, and N. R. Jennings. Determining successful negotiation strategies: an evolutionary approach. In Y. Demazeau, editor, Proceedings of the 3rd International Conference on Multi-Agent Systems (ICMAS-98), pages 182--189, Paris, France, 1998. IEEE Press.]]
[22]
S. Matwin, T. Szapiro, and K. Haigh. Genetic algorithm approach to a negotiation support system. IEEE Transactions on Systems Man and Cybernetics, 21(1):102--114, January-February 1991.]]
[23]
H. Raiffa. The Art and Science of Negotiation. Harvard University Press, 1982.]]
[24]
J. Rosenschein and G. Zlotkin. Task oriented domains. In Rules of Encounter: Designing Conventions for Automated Negotiation among Computers, pages 29--52. MIT Press, Cambridge, Massachusetts, 1994.]]
[25]
Bonnie Rubenstein-Montano and Ross A. Malaga. A Weighted Sum Genetic Algorithm to Support Multiple-Party Multi-Objective Negotiations. IEEE Transactions on Evolutionary Computation, 6(4):366--377, August 2002.]]
[26]
A. Rubinstein. Perfect equilibrium in a bargaining model. Econometrica, 50(1):97--109, 1982.]]
[27]
C. Sierra, P. Faratin, and N. R. Jennings. Deliberative automated negotiators using fuzzy similarities. In Proceedings of the EUSFLAT-ESTYLF Joint Conference on Fuzzy Logic, pages 155--158, Palma de Mallorca, Spain, 1999.]]
[28]
K. Sycara. Multi-agent compromise via negotiation. In L. Gasser and M. Huhns, editors, Distributed Artificial Intelligence II, pages 119--139. Morgan Kaufmann, 1989.]]
[29]
Paul Tremblett. Java and UDDI registries. Dr. Dobb's Journal of Software Tools, 27(9):34, 37--40, September 2002.]]
[30]
J. von Neumann and O. Morgenstern. The Theory of Games and Economic Behaviour. Princeton University Press, 1994.]]
[31]
W3C. Web Services Activity, 2004. Available from http: //www.w3.org/T R/2004/NOT E-ws-arch-20040211/.]]
[32]
M. Wooldridge and N. Jennings. Intelligent Agents: Theory and Practice. Knowledge Engineering Review, 10(2):115--152, 1995.]]
[33]
D. Zeng and K. Sycara. Bayesian learning in negotiation. International Journal of Human-Computer Studies, 48(1):125--141, 1998.]]
[34]
F. Zeuthen. Problem of Monopoly and Economic Warfare. Routledge and Kegan-Pail, London, U.K., 1967.]]

Cited By

View all
  • (2016)Learning about the opponent in automated bilateral negotiationAutonomous Agents and Multi-Agent Systems10.1007/s10458-015-9309-130:5(849-898)Online publication date: 1-Sep-2016
  • (2013)A social approach for learning agentsExpert Systems with Applications: An International Journal10.1016/j.eswa.2012.10.00840:5(1902-1916)Online publication date: 1-Apr-2013
  • (2013)Implications and Solution for High-Speed Business ArchitectureAgent and Multi-Agent Systems in Distributed Systems - Digital Economy and E-Commerce10.1007/978-3-642-35208-9_7(125-136)Online publication date: 2013
  • Show More Cited By

Index Terms

  1. Adaptive negotiation agents for e-business

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICEC '05: Proceedings of the 7th international conference on Electronic commerce
    August 2005
    957 pages
    ISBN:1595931120
    DOI:10.1145/1089551
    • Conference Chairs:
    • Qi Li,
    • Ting-Peng Liang
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 15 August 2005

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. automated negotiation
    2. e-business
    3. evolutionary learning
    4. intelligent agents

    Qualifiers

    • Article

    Acceptance Rates

    Overall Acceptance Rate 150 of 244 submissions, 61%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)1
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 15 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2016)Learning about the opponent in automated bilateral negotiationAutonomous Agents and Multi-Agent Systems10.1007/s10458-015-9309-130:5(849-898)Online publication date: 1-Sep-2016
    • (2013)A social approach for learning agentsExpert Systems with Applications: An International Journal10.1016/j.eswa.2012.10.00840:5(1902-1916)Online publication date: 1-Apr-2013
    • (2013)Implications and Solution for High-Speed Business ArchitectureAgent and Multi-Agent Systems in Distributed Systems - Digital Economy and E-Commerce10.1007/978-3-642-35208-9_7(125-136)Online publication date: 2013
    • (2010)Service Oriented Architecture and Agents: Parallels and OpportunitiesAgent and Multi-agent Technology for Internet and Enterprise Systems10.1007/978-3-642-13526-2_2(25-48)Online publication date: 2010
    • (2008)Or Best OfferProceedings of the 2008 IEEE Workshop on Policies for Distributed Systems and Networks10.1109/POLICY.2008.39(173-180)Online publication date: 2-Jun-2008
    • (2008)A Multi-Issue Negotiation Mechanism for Bounded Rational NegotiatorsProceedings of the Fifth International Conference on Information Technology: New Generations10.1109/ITNG.2008.177(156-161)Online publication date: 7-Apr-2008
    • (2008)A Multi-issue Negotiation Mechanism with Interdependent Negotiation IssuesProceedings of the Second International Conference on Digital Society10.1109/ICDS.2008.35(55-59)Online publication date: 10-Feb-2008
    • (2007)A Multi-agent, Multi-object and Multi-attribute Intelligent Negotiation ModelProceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 0310.1109/FSKD.2007.64(440-446)Online publication date: 24-Aug-2007
    • (2007)LEARNING DRIFTING NEGOTIATIONSApplied Artificial Intelligence10.1080/0883951070152695421:9(861-881)Online publication date: 1-Oct-2007
    • (2007)Towards a web services and intelligent agents-based negotiation system for B2B eCommerceElectronic Commerce Research and Applications10.1016/j.elerap.2006.06.0076:3(260-273)Online publication date: 1-Oct-2007

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media