Abstract
Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent’s knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.
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References
Al-Axhmaway, W.H., El-Sisi, A.B., Nassar, H.M., Ismail, N.A.: Bilateral Agent Negotiation for E-Commerce Based on Fuzzy Logic. In: ICCES 2007International Conference on Computer Engineering and Systems (2007)
Faratin, P., Sierra, C., Jennings, N.R., Buckle, P.: Designing Responsive and Deliberative Automated Negotiators. In: Proc. AAAI Workshop on Negotiation: Settling Conflicts and Identifying Opportunities, Orlando, pp. 12–18 (1999)
Lonmuscio, A., Wooldridge, M., Jennings, N.: A classification scheme for negotiation in electronic commerce. International Journal of Group Decision and Negotiation 12(1), 31–56 (2003)
Fatima, S.S., Wooldridge, M., Jennings, N.R.: Multi-issue negotiation under time constraints. In: Proceedings of the First International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2002), Bologna, Italy (2002)
Fatima, S.S., Wooldridge, M., Jennings, N.R.: An agenda- based framework for multi- issue negotiation. Artificial Intelligence 152(1), 1–45 (2004)
Wang, X., Shen, X., Georganas, N.D.: A Fuzzy Logic Based Intelligent Negotiation Agent (FINA) In ECommerce. In: Proc. IEEE Canadian Conference on Electrical and Computer Engineering, Ottawa, ON, Canada (2006)
Yu, T.-J., Robert Lai, K., Lin, M.-W., Kao, B.-R.: A Fuzzy Constraint-Directed Autonomous Learning to Support Agent Negotiation. In: 3rd International Conference on Autonomic and Autonomous Systems, ICAS (2007)
Jennings, N.R., Faratin, P., Lomuscio, A.R., et al.: Automated negotiation: prospects, methods and challenges. International Journal of Group Decision and Negotiation 10(2), 199–215 (2001)
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© 2009 Springer-Verlag Berlin Heidelberg
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Zuo, B., Zheng, S., Wu, H. (2009). Multi-issue Agent Negotiation Based on Fairness. In: Liu, W., Luo, X., Wang, F.L., Lei, J. (eds) Web Information Systems and Mining. WISM 2009. Lecture Notes in Computer Science, vol 5854. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05250-7_18
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DOI: https://doi.org/10.1007/978-3-642-05250-7_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-05249-1
Online ISBN: 978-3-642-05250-7
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