Bayesian learning in bilateral multi-issue negotiation and its application in MAS-based electronic commerce
作者： Yuan-Da Cao , Jian Li
DOI: 10.1109/IAT.2004.40
关键词:
摘要: With the rapid development of multi-agent systems (MAS), automatic negotiation is often needed. But because incomplete information agents have in systems, efficiency rather low. To overcome this problem, a Bayesian learning algorithm presented to learn agent enhance efficiency. The applied bilateral multi-issue MAS-based e-commerce. Experiments show that it can help negotiate more efficiently.
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