Error thresholds in genetic algorithms
Error thresholds in genetic algorithms
复制标题
DOI：
10.1162/evco.2006.14.2.157
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发表时间：
2006-06-01
影响因子：
6.8
通讯作者：
Ochoa, Gabriela
中科院分区：
文献类型：
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作者：
Ochoa, Gabriela
复制的错误阈值是准物种进化模型中的一个重要概念；它是一个临界突变率(错误率)，超过这个阈值，进化过程中获得的结构被破坏的频率比选择能够复制它们的频率更高。当突变率超过这个临界值时，就会发生一场错误灾难，基因组信息就会无可挽回地丢失。因此，研究改变这种大小的因素在进化研究中具有重要的意义。在这里，我们使用遗传算法而不是准物种模型作为基本的进化模型，并探索在复杂地形上进化的有限比特串群体中是否存在错误阈值现象。我们的实验结果验证了遗传算法中误差阈值的出现。通过这种方式，这个概念从分子进化带入进化计算。我们还研究了修改最显著的进化参数对该临界值大小的影响，发现误差阈值主要取决于选择压力和基因长度。
The error threshold of replication is an important notion in the quasispecies evolution model; it is a critical mutation rate (error rate) beyond which structures obtained by an evolutionary process are destroyed more frequently than selection can reproduce them. With mutation rates above this critical value, an error catastrophe occurs and the genomic information is irretrievably lost. Therefore, studying the factors that alter this magnitude has important implications in the study of evolution. Here we use a genetic algorithm, instead of the quasispecies model, as the underlying model of evolution, and explore whether the phenomenon of error thresholds is found on finite populations of bit strings evolving on complex landscapes. Our empirical results verify the occurrence of error thresholds in genetic algorithms. In this way, this notion is brought from molecular evolution to evolutionary computation. We also study the effect of modifying the most prominent evolutionary parameters on the magnitude of this critical value, and found that error thresholds depend mainly on the selection pressure and genotype length.