Soule T, Foster J A
Computer Science Dept., St. Cloud State University, Engineering and Computing Center, MN 56301-4498, USA.
Evol Comput. 1998 Winter;6(4):293-309.
Parsimony pressure, the explicit penalization of larger programs, has been increasingly used as a means of controlling code growth in genetic programming. However, in many cases parsimony pressure degrades the performance of the genetic program. In this paper we show that poor average results with parsimony pressure are a result of "failed" populations that overshadow the results of populations that incorporate parsimony pressure successfully. Additionally, we show that the effect of parsimony pressure can be measured by calculating the relationship between program size and performance within the population. This measure can be used as a partial indicator of success or failure for individual populations.
简约压力，即对更大程序的明确惩罚，已越来越多地被用作控制遗传编程中代码增长的一种手段。然而，在许多情况下，简约压力会降低遗传程序的性能。在本文中，我们表明，使用简约压力时平均结果不佳是由于“失败”的种群掩盖了成功纳入简约压力的种群的结果。此外，我们表明，可以通过计算种群内程序大小与性能之间的关系来衡量简约压力的效果。这种度量可以用作单个种群成功或失败的部分指标。
