On the Interaction of Adaptive Population Control with Cumulative Step-Size Adaptation
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| Main Authors: | , |
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| Format: | Preprint |
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2024
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| _version_ | 1866916417986625536 |
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| author | Omeradzic, Amir Beyer, Hans-Georg |
| author_facet | Omeradzic, Amir Beyer, Hans-Georg |
| contents | Three state-of-the-art adaptive population control strategies (PCS) are theoretically and empirically investigated for a multi-recombinative, cumulative step-size adaptation Evolution Strategy $(μ/μ_I, λ)$-CSA-ES. First, scaling properties for the generation number and mutation strength rescaling are derived on the sphere in the limit of large population sizes. Then, the adaptation properties of three standard CSA-variants are studied as a function of the population size and dimensionality, and compared to the predicted scaling results. Thereafter, three PCS are implemented along the CSA-ES and studied on a test bed of sphere, random, and Rastrigin functions. The CSA-adaptation properties significantly influence the performance of the PCS, which is shown in more detail. Given the test bed, well-performing parameter sets (in terms of scaling, efficiency, and success rate) for both the CSA- and PCS-subroutines are identified. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_00595 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | On the Interaction of Adaptive Population Control with Cumulative Step-Size Adaptation Omeradzic, Amir Beyer, Hans-Georg Neural and Evolutionary Computing Three state-of-the-art adaptive population control strategies (PCS) are theoretically and empirically investigated for a multi-recombinative, cumulative step-size adaptation Evolution Strategy $(μ/μ_I, λ)$-CSA-ES. First, scaling properties for the generation number and mutation strength rescaling are derived on the sphere in the limit of large population sizes. Then, the adaptation properties of three standard CSA-variants are studied as a function of the population size and dimensionality, and compared to the predicted scaling results. Thereafter, three PCS are implemented along the CSA-ES and studied on a test bed of sphere, random, and Rastrigin functions. The CSA-adaptation properties significantly influence the performance of the PCS, which is shown in more detail. Given the test bed, well-performing parameter sets (in terms of scaling, efficiency, and success rate) for both the CSA- and PCS-subroutines are identified. |
| title | On the Interaction of Adaptive Population Control with Cumulative Step-Size Adaptation |
| topic | Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2410.00595 |