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Mirrored Orthogonal Sampling for Covariance Matrix Adaptation Evolution Strategies

机译：协方差矩阵适应进化策略的镜像正交采样

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摘要

Generating more evenly distributed samples in high dimensional search spaces is the major purpose of the recently proposed mirrored sampling technique for evolution strategies. The diversity of the mutation samples is enlarged and the convergence rate is therefore improved by the mirrored sampling. Motivated by the mirrored sampling technique, this article introduces a new derandomized sampling technique called mirrored orthogonal sampling. The performance of this new technique is both theoretically analyzed and empirically studied on the sphere function. In particular, the mirrored orthogonal sampling technique is applied to the well-known Covariance Matrix Adaptation Evolution Strategy (CMA-ES). The resulting algorithm is experimentally tested on the well-known Black-Box Optimization Benchmark (BBOB). By comparing the results from the benchmark, mirrored orthogonal sampling is found to outperform both the standard CMA-ES and its variant using mirrored sampling.
机译：在高维搜索空间中生成分布更均匀的样本是最近提出的用于进化策略的镜像采样技术的主要目的。突变样本的多样性得以扩大，因此通过镜像采样可以提高收敛速度。受镜像采样技术的启发，本文介绍了一种称为镜像正交采样的新的非随机采样技术。从球面函数的角度对这一新技术的性能进行了理论分析和经验研究。特别地，将镜像正交采样技术应用于众所周知的协方差矩阵适应发展策略（CMA-ES）。生成的算法在著名的黑匣子优化基准（BBOB）上进行了实验测试。通过比较基准测试的结果，发现镜像正交采样的性能优于标准CMA-ES及其使用镜像采样的变体。

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