An improved multiagent reinforcement learning algorithm

被引：0

作者：

Meng, XP ^{[1
]}

Babuska, R ^{[1
]}

Busoniu, L ^{[1
]}

Chen, Y ^{[1
]}

Tan, WY ^{[1
]}

机构：

[1] Changchun Inst Technol, Dept Elect Engn, Changchun, Peoples R China

来源：

2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, Proceedings | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An improved reinforcement learning algorithm is proposed in this paper. This algorithm is based on linear programming method for finding the best-response policy. A pursuit example is tested and the results show that this algorithm has some properties, such as easy computation, simple operation procedure and can guarantee an good learning convergence.

引用

页码：337 / 343

页数：7

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