Title :
A learning-based multistage negotiation model
Author :
Wang, Li-Ming ; Huang, Hou-Kuan ; Chai, Yu-Mei
Author_Institution :
Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ., China
Abstract :
This work presents a learning-based multistage model for multi-issue negotiation with deadline in an incomplete information setting based on intentional agents. The model describes negotiation over the price of multi-issue. It decomposes multi-issue negotiation into multistage negotiation, and each stage has the same size. The order and number of stages are decided exogenously, and the order of issues in each stage is decided endogenously. The optimal negotiation agenda for a given decomposition of the bargaining problem based on the same size of stages is presented. In particular, the model also supports the learning capability of participating agents by building a learning system (LS) for them.
Keywords :
electronic commerce; learning systems; multi-agent systems; bargaining problem; intentional agents; learning system; learning-based multistage negotiation model; optimal negotiation agenda; Bayesian methods; Consumer electronics; Contracts; Decision making; Electronic mail; Information technology; Learning systems; Packaging; Performance analysis; Protocols;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1380633
