Smith P W, Harries K
Computer Science Department, City University, London, UK.
Evol Comput. 1998 Winter;6(4):339-60.
Previous work on introns and code growth in genetic programming is expanded on and tested experimentally. Explicitly defined introns are introduced to tree-based representations as an aid to measuring and evaluating intron behavior. Although it is shown that introns do create code growth, they are not its only cause. Removing introns merely decreases the growth rate; it does not eliminate it. By systematically negating various forms of intron behavior, a deeper understanding of the causes of code growth is obtained, leading to the development of a system that keeps unnecessary bloat to a minimum. Alternative selection schemes and recombination operators are examined and improvements demonstrated over the standard selection methods in terms of both performance and parsimony.
先前关于遗传编程中内含子和代码增长的研究工作得到了扩展，并进行了实验测试。明确界定的内含子被引入基于树的表示法中，以辅助测量和评估内含子行为。虽然研究表明内含子确实会导致代码增长，但它们并非唯一原因。去除内含子只会降低增长速度，而不会消除增长。通过系统地否定各种形式的内含子行为，能更深入地理解代码增长的原因，从而开发出一个将不必要的膨胀降至最低的系统。研究了替代选择方案和重组算子，并证明在性能和简约性方面优于标准选择方法。
