Perceptive particle swarm optimisation

被引：3
|
作者：
Kaewkamnerdpong, B [1 ]
Bentley, PJ [1 ]
机构：
[1] UCL, Dept Comp Sci, London WC1E 6BT, England
来源：
ADAPTIVE AND NATURAL COMPUTING ALGORITHMS | 2005年
关键词：
D O I：
10.1007/3-211-27389-1_62
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Conventional particle swarm optimisation relies on exchanging information through social interaction among individuals. However for real-world problems involving control of physical agents (i.e., robot control), such detailed social interaction is not always possible. In this study, we propose the Perceptive Particle Swarm Optimisation algorithm, in which both social interaction and environmental interaction are increased to mimic behaviours of social animals more closely.
引用
收藏
页码：259 / 263
页数：5
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