Title :
Bayesian learning in bilateral multi-issue negotiation and its application in MAS-based electronic commerce
Author :
Li, Jian ; Cao, Yuan-Da
Author_Institution :
Dept. of Comput. Sci., Beijing Inst. of Technol., China
Abstract :
With the rapid development of multi-agent systems (MAS), automatic negotiation is often needed. But because of incomplete information agents have in the systems, the efficiency of negotiation is rather low. To overcome this problem, a Bayesian learning algorithm is presented to learn incomplete information of the negotiation agent to enhance the negotiation efficiency. The algorithm is applied to bilateral multi-issue negotiation in MAS-based e-commerce. Experiments show that it can help agents to negotiate more efficiently.
Keywords :
belief networks; electronic commerce; learning (artificial intelligence); multi-agent systems; Bayesian learning; automatic negotiation; bilateral multi-issue negotiation; e-commerce; electronic commerce; multi-agent systems; negotiation agent; Application software; Bayesian methods; Computer science; Costs; Delay; Electronic commerce; Least squares methods; Multiagent systems; Proposals; Protocols;
Conference_Titel :
Intelligent Agent Technology, 2004. (IAT 2004). Proceedings. IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2101-0
DOI :
10.1109/IAT.2004.1342990
