Abstract
Negotiating agents play a key role in e-markets and become more popular. However, in much existing work, the e-markets are assumed to be closed and static, which is unrealistic. To address the issue, this paper developed negotiating agents that can adapt their negotiation strategies, outcome expectations, offer evaluations, and counter-offers generations in dynamic, open e-markets. Also, the proposed agents can generate multiple counter-offers according to different preferences so as to further improve their negotiation outcomes. Finally, the experimental results show the improvements on agents' profits by employing our negotiation model. © 2011 Springer-Verlag.
Cite
CITATION STYLE
Ren, F., Zhang, M., Luo, X., & Soetanto, D. (2011). A parallel, multi-issue negotiation model in dynamic e-markets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7106 LNAI, pp. 442–451). https://doi.org/10.1007/978-3-642-25832-9_45
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