摘要
基于细胞克隆选择学说 ,系统阐述了用于人工智能的多克隆算子 将多克隆算子用于进化算法 ,提出了改进的进化策略算法———免疫多克隆策略算法 ,并基于Markov链的有关性质 ,证明了该算法的收敛性 理论分析和仿真实验表明 ,与传统的进化策略算法相比 ,该算法有效克服了早熟问题 ,保持了抗体的多样性 。
Based on the clonal selection theory the main mechanisms of clone used in the field of artificial intelligence are analyzed in this paper An improved evolutionary strategies algorithm, immunity poly clonal strategy algorithm (IPSA), is put forward Compared with the classical evolutionary strategies (CES), IPSA is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like multi objective optimization, and the results are better Using the theories of Markov chain, it is proved that IPSA is convergent
出处
《计算机研究与发展》
EI
CSCD
北大核心
2004年第4期571-576,共6页
Journal of Computer Research and Development
基金
国家自然科学基金项目 (60 13 3 0 10 )
关键词
克隆选择
进化算法
进化策略
MARKOV链
clonal selection
evolutionary algorithm
evolutionary strategies
Markov chain
