Resource sharing and coevolution in evolving cellular automata
Resource sharing and coevolution in evolving cellular automata
复制标题
进化元胞自动机中的资源共享和协同进化
DOI：
10.1109/4235.887238
复制
发表时间：
1999
期刊：
影响因子：
--
通讯作者：
J. Crutchfield
中科院分区：
文献类型：
--
作者：
Justin Werfel;Melanie Mitchell;J. Crutchfield
协同进化，人口之间的候选解决方案和人口的测试用例，已受到越来越多的关注，作为一个有前途的生物启发的方法，提高性能的进化计算技术。然而，对共同进化的研究结果是喜忧参半的。到目前为止，一个看起来更令人印象深刻的结果是Juille和Pollack（1998）通过共同进化证明了进化细胞自动机来执行分类任务的改进。然而，他们的研究与大多数其他关于共同进化的研究一样，没有调查引起观察到的改善的机制。在本文中，我们更深入地探讨了这些观察到的改进的原因，并提出了经验证据，与Juille和Pollack所声称的相反，所看到的大部分改进是由于他们的“资源共享”技术，而不是共同进化。我们还提出了经验证据，资源共享的工作，至少在一定程度上，通过保持人口的多样性。
Coevolution, between a population of candidate solutions and a population of test cases, has received increasing attention as a promising biologically inspired method for improving the performance of evolutionary computation techniques. However, the results of studies of coevolution have been mixed. One of the seemingly more impressive results to date was the improvement via coevolution demonstrated by Juille and Pollack (1998) on evolving cellular automata to perform a classification task. Their study, however, like most other studies on coevolution, did not investigate the mechanisms giving rise to the observed improvements. In this paper, we probe more deeply into the reasons for these observed improvements and present empirical evidence that, in contrast to what was claimed by Juille and Pollack, much of the improvement seen was due to their "resource sharing" technique rather than to coevolution. We also present empirical evidence that resource sharing works, at least in part, by preserving diversity in the population.