Parallel learning evolutionary algorithm based on neural network ensemble

被引：0
|
作者：
Xiao, Sha [1 ]
Yu, Dong [1 ]
Li, Yibin [1 ]
机构：
[1] Shandong Univ, Sch Control Sci & Engn, Jinan, Shandong Prov, Peoples R China
来源：
2006 IEEE INTERNATIONAL CONFERENCE ON INFORMATION ACQUISITION, VOLS 1 AND 2, CONFERENCE PROCEEDINGS | 2006年
关键词：
neural network ensemble; evolutionary algorithm; parallel;
D O I：
10.1109/ICIA.2006.305824
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new parallel evolutionary algorithm based on neural network (NN) ensemble is proposed for mobile robots. The robot controller has a reconfigurable structure with user-defined sensor suite, which corresponds to a typical network. NN ensemble is evolved to optimize the optimal sub-networks including both learning rules and combining weights dynamically. The experiment results show that the genetic algorithm based NN ensemble has stronger evolutionary capacity and higher learning efficiency of parallelism compared with the general genetic algorithm.
引用
收藏
页码：70 / 74
页数：5
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