Abstract
Human negotiators can persuade the opponents to revise their beliefs in order to maximise the chance of reaching an agreement. Existing negotiation models are weak in supporting persuasive negotiations. This paper illustrates an adaptive and persuasive negotiation agent model, which is underpinned by a belief revision logic. These belief-based negotiation agents are able to learn from the changing negotiation contexts and persuade their opponents to change their positions. Our preliminary experiments show that the belief-based adaptive negotiation agents outperform a classical negotiation model under time pressure.
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References
Lomuscio, A.R., Jennings, N.R.: A classification scheme for negotiation in electronic commerce. Journal of Group Decision and Negotiation 12, 31–56 (2003)
von Neumann, J., Morgenstern, O.: The Theory of Games and Economic Behaviour. Princeton University Press, Princeton (1994)
Parsons, S., Sierra, C., Jennings, N.: Agents that reason and negotiate by arguing. Journal of Logic and Computation 8, 261–292 (1998)
Kraus, S., Sycara, K., Evenchik, A.: Reaching agreements through argumentation: A logical model and implementation. Artificial Intelligence 104, 1–69 (1998)
Barbuceanu, M., Lo, W.K.: Multi-attribute utility theoretic negotiation for electronic commerce. In: Dignum, F.P.M., Cortés, U. (eds.) AMEC 2000. LNCS (LNAI), vol. 2003, pp. 15–30. Springer, Heidelberg (2001)
Alchourrón, C., Gärdenfors, P., Makinson, D.: On the logic of theory change: partial meet contraction and revision functions. Journal of Symbolic Logic 50, 510–530 (1985)
Gärdenfors, P., Makinson, D.: Revisions of knowledge systems using epistemic entrenchment. In: Vardi, M.Y. (ed.) Proceedings of the Second Conference on Theoretical Aspects of Reasoning About Knowledge, Pacific Grove, California, pp. 83–95. Morgan Kaufmann, San Francisco (1988)
Williams, M.A.: Anytime belief revision. In: Pollack, M.E. (ed.) Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, Nagoya, Japan, pp. 74–79. Morgan Kaufmann Publishers, San Francisco (1997)
Spohn, W.: Ordinal conditional functions: A dynamic theory of epistemic states. In: Harper, W., Skyrms, B. (eds.) Causation in Decision, Belief Change and Statistics, vol. 2, pp. 105–134. D. Reidel, Dordrecht (1987)
Lau, R.: Context-Sensitive Text Mining and Belief Revision for Intelligent Information Retrieval on the Web. Web Intelligence and Agent Systems An International Journal 1, 1–22 (2003)
Gärdenfors, P., Makinson, D.: Nonmonotonic inference based on expectations. Artificial Intelligence 65, 197–245 (1994)
Krovi, R., Graesser, A., Pracht, W.: Agent behaviors in virtual negotiation environments. IEEE Transactions on Systems, Man, and Cybernetics 29, 15–25 (1999)
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Lau, R.Y.K., Chan, S.Y. (2004). Towards Belief Revision Logic Based Adaptive and Persuasive Negotiation Agents. In: Zhang, C., W. Guesgen, H., Yeap, WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science(), vol 3157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28633-2_64
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DOI: https://doi.org/10.1007/978-3-540-28633-2_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22817-2
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