A novel quantum-inspired immune clonal algorithm with the evolutionary game approach

被引：13
|
作者：
Wu, Qiuyi [1 ]
Jiao, Licheng [1 ]
Li, Yangyang [1 ]
Deng, Xiaozheng [1 ]
机构：
[1] Xidian Univ, Inst Intelligent Informat Proc, Minist Educ China, Key Lab Intelligent Percept & Image Understanding, Xian 710071, Peoples R China
来源：
PROGRESS IN NATURAL SCIENCE-MATERIALS INTERNATIONAL | 2009年 / 19卷 / 10期
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Game theory; Evolutionary game; Replicator dynamics; Quantum-inspired optimization; Artificial immune system;
D O I：
10.1016/j.pnsc.2009.02.007
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The quantum-inspired immune clonal algorithm (QICA) is a rising intelligence algorithm. Based on evolutionary game theory and QICA, a quantum-inspired immune algorithm embedded with evolutionary game (EGQICA) is proposed to solve combination optimization problems. In this paper, we map the quantum antibody's finding the optimal solution to player's pursuing maximum utility by choosing strategies in evolutionary games. Replicator dynamics is used to model the behavior of the quantum antibody and the memory mechanism is also introduced in this work. Experimental results indicate that the proposed approach maintains a good diversity and achieves superior performance. (C) 2009 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.
引用
收藏
页码：1341 / 1347
页数：7
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