An Improved Bayesian Learning Method for Multi-agent System

被引：1
|
作者：
Dai Sheng-Hui [1 ]
Zhu Xue-Qin [1 ]
Gui Ying [1 ]
Xu Hong-Zhen [1 ]
机构：
[1] E China Inst Technol, Dept Comp Sci & Technol, Shanghai 344000, Peoples R China
来源：
INTERNATIONAL JOURNAL OF ONLINE ENGINEERING | 2015年 / 11卷 / 09期
基金：
中国国家自然科学基金;
关键词：
Multi-agent system; Intelligent agent; Agent learning; Bayesian learning;
D O I：
10.3991/ijoe.v11i9.5071
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
A multi-agent coordinate ion is addressed in urban traffic control, which uses the recursive modeling method (RMM) that enables an agent to select its rational act ion by examining with other agents by modeling their decision making in a distributed multi-agent environment. Bayesian learning is used in conjunction with RMM for belief update. Based on this method, a multi-agent traffic control system is established and the results rated its effective.
引用
收藏
页码：82 / 88
页数：7
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