摘要
克隆选择算法收敛性研究是免疫计算领域中一个复杂而重要的问题,但是有关收敛性的研究结果还相对较少.本文综述有关克隆选择算法收敛性方法研究的近期理论成果,分别概述齐次马氏链模型、纯概率方法和鞅论三种算法收敛性研究方法的模型并分析它们的优缺点,以期推动克隆选择算法收敛性理论研究的更深入发展.
It is complicated and important to study the convergence of clonal selection algorithms in the field of immune computation.However,there are few results about it.Recent developments on the convergence analysis on clonal selection algorithm are reviewed.While the main focus of this review is placed on the existing convergence analysis methods such as the homogeneous Markov chain model,pure probabilistic method and martingale theory.The advantages and disadvantages of these models are analyzed in order to promote further development of the convergence theory study for clonal selection algorithm.
出处
《信息与控制》
CSCD
北大核心
2011年第2期232-236,共5页
Information and Control
基金
中国博士后科学基金资助项目(200904501048)
江苏省博士后基金资助项目(0901076C)
关键词
克隆选择算法
收敛性
马尔可夫链
下鞅
依概率收敛
clonal selection algorithm
convergence
Markov chain
submartingale
probabilistic convergence
