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. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Lau, R. Y. K., & Chan, S. Y. (2004). Towards belief revision logic based adaptive and persuasive negotiation agents. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3157, pp. 605–614). Springer Verlag. https://doi.org/10.1007/978-3-540-28633-2_64
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