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The Cooperative Royal Road: Avoiding Hitchhiking

机译:皇家合作之路:避免搭便车

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We propose using the so called Royal Road functions as test functions for cooperative co-evolutionary algorithms (CCEAs). The Royal Road functions were created in the early 90's with the aim of demonstrating the superiority of genetic algorithms over local search methods. Unexpectedly, the opposite was found to be true. The research deepened our understanding of the phenomenon of hitchhiking where unfavorable alleles may become established in the population following an early association with an instance of a highly fit schema. Here, we take advantage of the modular and hierarchical structure of the Royal Road functions to adapt them to a co-evolutionary setting. Using a multiple population approach, we show that a CCEA easily outperforms a standard genetic algorithm on the Royal Road functions, by naturally overcoming the hitchhiking effect. Moreover, we found that the optimal number of sub-populations for the CCEA is not the same as the number of components that the function can be linearly separated into, and propose an explanation for this behavior. We argue that this class of functions may serve in foundational studies of cooperative co-evolution.
机译:我们建议使用所谓的Royal Road函数作为合作协同进化算法(CCEA)的测试函数。 Royal Road函数创建于90年代初,目的是证明遗传算法优于本地搜索方法。出乎意料的是,事实恰恰相反。这项研究加深了我们对搭便车现象的理解,在这种现象中,在与高度适合的模式实例早期相关之后,人群中可能会形成不利的等位基因。在这里,我们利用皇家路功能的模块化和层次结构来使它们适应共同进化的环境。使用多种群方法,我们证明了CCEA通过自然克服搭便车效应,在皇家路功能上轻松胜过标准遗传算法。此外,我们发现CCEA的最佳子群体数量与功能可以线性分离成的组件数量不同,并对此行为提出了解释。我们认为,此类功能可能在合作协同进化的基础研究中发挥作用。

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