Measuring evolvability in evolutionary fuzzy robotics

Seung-Ik Lee, Sung-Bae Cho
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Abstract

This paper illustrates the evolutionary adaptive process of the rules of a fuzzy controller evolved by a genetic algorithm. Evolutionary activity and schema analysis are used to evaluate and analyze the evolution. The analysis shows that the evolution has been adaptive and final fuzzy rules have evolved from adaptive ones of earlier generations.
进化模糊机器人的可进化性测量
本文阐述了用遗传算法进化模糊控制器规则的进化自适应过程。进化活动和模式分析用于评估和分析进化。分析表明,模糊规则的进化是自适应的,最终的模糊规则是由前几代的自适应规则进化而来的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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