Using Genetic Algorithms to Explore Pattern Recognition in the Immune System

被引:142
作者
Forrest, Stephanie [1 ]
Javornik, Brenda [1 ]
Smith, Robert E. [2 ]
Perelson, Alan S. [3 ]
机构
[1] Univ New Mexico, Dept Comp Sci, Albuquerque, NM 87131 USA
[2] Univ Alabama, Dept Engn Mech, Tuscaloosa, AL 35487 USA
[3] Univ Calif Los Alamos Natl Lab, Div Theoret, Los Alamos, NM 87545 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
genetic algorithms; immune system; pattern recognition; fitness sharing;
D O I
10.1162/evco.1993.1.3.191
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes an immune system model based on binary strings. The purpose of the model is to study the pattern-recognition processes and learning that take place at both the individual and species levels in the immune system. The genetic algorithm (GA) is a central component of the model. The paper reports simulation experiments on two-pattern-recognition problems that are relevant to natural immune systems. Finally, it reviews the relation between the model and explicit fitness-sharing techniques for genetic algorithms, showing that the immune system model implements a form of implicit fitness sharing.
引用
收藏
页码:191 / 211
页数:21
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