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一种基于模仿者动态模型的免疫算法
引用本文:谭光兴,毛宗源. 一种基于模仿者动态模型的免疫算法[J]. 计算机工程与应用, 2006, 42(2): 55-57,190
作者姓名:谭光兴  毛宗源
作者单位:华南理工大学自动化科学与工程学院,广州,510640;华南理工大学自动化科学与工程学院,广州,510640
基金项目:广东省广州市科技攻关项目
摘    要:免疫网络理论在人工智能中起着十分重要的作用。该文在已有的研究基础上,根据进化博弈的思想,通过改进亲和力计算方法,综合表达函数值、距离和匹配程度的信息,并以抗体的浓度作为适应度,提出了基于模仿者动态模型的免疫算法。两类典型的测试函数的数字仿真实验结果表明,该算法有效地提高了全局搜索性能和收敛速度。

关 键 词:模仿动态  免疫网络  进化博弈  免疫算法  优化
文章编号:1002-8331-(2006)02-0055-03

An Immune Algorithm Based on Replicator Dynamic Model
Tan Guangxing,Mao Zongyuan. An Immune Algorithm Based on Replicator Dynamic Model[J]. Computer Engineering and Applications, 2006, 42(2): 55-57,190
Authors:Tan Guangxing  Mao Zongyuan
Affiliation:College of Automation Science and Engineering, South China Univ. of Tech., Guangzhou 510640
Abstract:Immune networks theory plays an important role in artificial intelligence.On the basis of some research results and evolutionary game theory,this paper proposes a calculative method to improve the affinity,and synthetically gives an expression of the information of function values,distances and matching grade.In this way,an improved immune algorithm based on replicator dynamic network model is presented by defining the concentration of antibodies as its fitness.Experiments of two kinds of typical testing function have been carried out,and the result shows the effective improvement of the global searching performance and the convergent speed of this method.
Keywords:replicator model  immune network  evolutionary game  immune algorithm   optimization
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