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Negotiation Life Cycle: An Approach in E-Negotiation with Prediction

  • Mohammad Irfan Bala
  • Sheetal Vij
  • Debajyoti Mukhopadhyay
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 248)

Abstract

With the exponential increase in the use of web services it has become more and more important to make the traditional negotiation process automated and intelligent. Various tactics have been given till date which determines the behavior of the software agents in the negotiation process. Here we have given lifecycle of the negotiation process and presented a custom scenario to understand it better. Recently the active area of research has been prediction of partner’s behavior which enables a negotiator to improve the utility gain for the adaptive negotiation agent and also achieve the agreement much quicker or look after much higher benefits. In this paper we review the various negotiation methods and the existing architecture. Although negotiation is practically very complex activity to automate without human intervention we have proposed architecture for predicting the opponents behavior which will take into consideration various factors which affect the process of negotiation. The basic concept is that the information about negotiators, their individual actions and dynamics can be used by software agents equipped with adaptive capabilities to learn from past negotiations and assist in selecting appropriate negotiation tactics.

Keywords

Electronic negotiation decision functions agent negotiation neural networks 

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References

  1. 1.
    Hou, C.: Predicting agents’ tactics in automated negotiation. In: Proc. IEEE/WIC/ACM Int’l Conf. Intelligent Agent Technology (IAT 2004), pp. 127–133 (2004)Google Scholar
  2. 2.
    Beheshti, R., Mozayani, N.: Predicting opponents offers in multi-agent negotiations using ARTMAP neural network. In: Second International Conference on Future Information Technology and Management Engineering, FITME 2009, pp. 600–603 (2009)Google Scholar
  3. 3.
    Carbonneau, R., Kersten, G.E., Vahidov, R.: Predicting opponent’s moves in electronic negotiations using neural networks. Expert Systems with Applications: An International Journal 34(2) (2008)Google Scholar
  4. 4.
    Mukhopadhyay, D., Vij, S., Tasare, S.: NAAS: Negotiation Automation Architecture with Buyers Behavior Pattern Prediction Component. In: Meghanathan, N., Nagamalai, D., Chaki, N. (eds.) Advances in Computing & Inform. Technology. AISC, vol. 176, pp. 425–434. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  5. 5.
    Ren, F., Zhang, M.: Prediction of partners behaviors in agent negotiation under open and dynamic environments. In: Proceedings of International Conferences on Web Intelligence and Intelligent Agent Technology, pp. 379–382 (2007)Google Scholar
  6. 6.
    Rau, H., Chen, C.-W., Shiang, W.-J., Lin, C.J.: Develop an adapted coordination strategy for negotiation in a buyer-driven E-marketplace. In: Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, pp. 3224–3229 (2008)Google Scholar
  7. 7.
    Zulkernine, F.H., Martin, P.: An adaptive and intelligent SLA negotiation system for web services. IEEE Transactions on Service Computing 4, 31–43 (2011)CrossRefGoogle Scholar
  8. 8.
    Haim, G., Kraus, S., Blumberg, Y.: Learning human negotiation behavior across cultures. In: Second International Working Conference on Human Factors and Computational Models in Negotiation (2010)Google Scholar
  9. 9.
    Zeng, D., Sycara, K.: Bayesian learning in negotiation. International Journal of Human-Computer Studies 48, 125–141 (1998)CrossRefGoogle Scholar
  10. 10.
    Brzostowski, J., Kowalczyk, R.: Predicting partner’s behaviour in agent negotiation. In: Proc. Int’l Joint Conf. Autonomous Agents and Multiagent Systems, pp. 355–361 (2006)Google Scholar
  11. 11.
    Mukun, C.: Multi-agent automated negotiation as a service. In: 7th International Conference on Service Systems and Service Management (ICSSSM), pp. 1–6 (2010)Google Scholar
  12. 12.
    Lin, R., Kraus, S.: Magazine communications of the ACM, vol. 53(1) (January 2010)Google Scholar
  13. 13.
    Roussaki, I., Papaioannou, I., Anagnostou, M.: Employing neural networks to assist negotiating intelligent agents. 2nd IET International Conference on Intelligent Environments 1, 101–110 (2006)Google Scholar
  14. 14.
    Park, S., Yang, S.-B.: An automated system based on Incremental learning with applicability toward multilateral negotiations. In: SICE-ICASE International Joint Conference, pp. 6001–6006 (2006)Google Scholar
  15. 15.
    Liu, N., Zheng, D., Xiong, Y.: Multi-agent negotiation model based on RBF neural network learning mechanism. In: International Symposium on Intelligent Information Technology Application Workshops, pp. 133–136 (2008)Google Scholar
  16. 16.
    Jazayeriy, H., Azmi-Murad, M., Sulaiman, M.N., Udzir, N.I.: A review on soft computing techniques in automated negotiation. Academic Journals for Scientific Research and Essays 6(24), 5100–5106 (2011)Google Scholar
  17. 17.
    Li, B., Ma, Y.: An auction-based negotiation model in intelligent multi-agent system. In: International Conference on Neural Networks and Brain, vol. 1, pp. 178–182 (2005)Google Scholar
  18. 18.
    Faratin, P.: Automated service negotiation between autonomous compositional agents. PhD thesis, Queen Mary & Westfield college, University of London, UK (2000)Google Scholar
  19. 19.
    Mukhopadhyay, D., Vij, S., Bala, M.I.: Automated Negotiation And Behavior Prediction. International Journal of Engineering Research & Technology 2(6), 1832–1838 (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mohammad Irfan Bala
    • 1
  • Sheetal Vij
    • 1
  • Debajyoti Mukhopadhyay
    • 2
  1. 1.Department of Computer EngineeringMaharashtra Institute of TechnologyPuneIndia
  2. 2.Department of Information TechnologyMaharashtra Institute of TechnologyPuneIndia

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