论文标题
快速移动的自然进化策略用于高维问题
Fast Moving Natural Evolution Strategy for High-Dimensional Problems
论文作者
论文摘要
在这项工作中，我们为高维黑盒优化问题提出了一种自然进化策略（NES）的新变体。提出的方法CR-FM-NES扩展了最近提出的最先进的NES，即快速移动的自然进化策略（FM-NES），以便适用于高维问题。 CR-FM-NES使用协方差矩阵的限制表示，而不是使用完整的协方差矩阵，同时继承了FM-NES的效率。协方差矩阵的限制表示使CR-FM-NES可以更新线性时间和空间复杂性中多元正态分布的参数，该参数可应用于高维问题。我们的实验结果表明，CR-FM-NES不会失去FM-NES的效率，相反，与FM-NES相比，在某些基准问题上，CR-FM-NES已取得了显着的加速。此外，我们使用200、600和1000维基准问题的数值实验表明，CR-FM-NES在可扩展的基线方法，VD-CMA和SEP-CMA上有效。
In this work, we propose a new variant of natural evolution strategies (NES) for high-dimensional black-box optimization problems. The proposed method, CR-FM-NES, extends a recently proposed state-of-the-art NES, Fast Moving Natural Evolution Strategy (FM-NES), in order to be applicable in high-dimensional problems. CR-FM-NES builds on an idea using a restricted representation of a covariance matrix instead of using a full covariance matrix, while inheriting an efficiency of FM-NES. The restricted representation of the covariance matrix enables CR-FM-NES to update parameters of a multivariate normal distribution in linear time and space complexity, which can be applied to high-dimensional problems. Our experimental results reveal that CR-FM-NES does not lose the efficiency of FM-NES, and on the contrary, CR-FM-NES has achieved significant speedup compared to FM-NES on some benchmark problems. Furthermore, our numerical experiments using 200, 600, and 1000-dimensional benchmark problems demonstrate that CR-FM-NES is effective over scalable baseline methods, VD-CMA and Sep-CMA.
