{"title":"Mutation Strength Adaptation of the $(μ/μ_I, λ)$-ES for Large Population Sizes on the Sphere Function","authors":"Amir Omeradzic, Hans-Georg Beyer","doi":"arxiv-2408.09761","DOIUrl":null,"url":null,"abstract":"The mutation strength adaptation properties of a multi-recombinative\n$(\\mu/\\mu_I, \\lambda)$-ES are studied for isotropic mutations. To this end,\nstandard implementations of cumulative step-size adaptation (CSA) and mutative\nself-adaptation ($\\sigma$SA) are investigated experimentally and theoretically\nby assuming large population sizes ($\\mu$) in relation to the search space\ndimensionality ($N$). The adaptation is characterized in terms of the\nscale-invariant mutation strength on the sphere in relation to its maximum\nachievable value for positive progress. %The results show how the different\n$\\sigma$-adaptation variants behave as $\\mu$ and $N$ are varied. Standard\nCSA-variants show notably different adaptation properties and progress rates on\nthe sphere, becoming slower or faster as $\\mu$ or $N$ are varied. This is shown\nby investigating common choices for the cumulation and damping parameters.\nStandard $\\sigma$SA-variants (with default learning parameter settings) can\nachieve faster adaptation and larger progress rates compared to the CSA.\nHowever, it is shown how self-adaptation affects the progress rate levels\nnegatively. Furthermore, differences regarding the adaptation and stability of\n$\\sigma$SA with log-normal and normal mutation sampling are elaborated.","PeriodicalId":501347,"journal":{"name":"arXiv - CS - Neural and Evolutionary Computing","volume":"3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Neural and Evolutionary Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.09761","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The mutation strength adaptation properties of a multi-recombinative
$(\mu/\mu_I, \lambda)$-ES are studied for isotropic mutations. To this end,
standard implementations of cumulative step-size adaptation (CSA) and mutative
self-adaptation ($\sigma$SA) are investigated experimentally and theoretically
by assuming large population sizes ($\mu$) in relation to the search space
dimensionality ($N$). The adaptation is characterized in terms of the
scale-invariant mutation strength on the sphere in relation to its maximum
achievable value for positive progress. %The results show how the different
$\sigma$-adaptation variants behave as $\mu$ and $N$ are varied. Standard
CSA-variants show notably different adaptation properties and progress rates on
the sphere, becoming slower or faster as $\mu$ or $N$ are varied. This is shown
by investigating common choices for the cumulation and damping parameters.
Standard $\sigma$SA-variants (with default learning parameter settings) can
achieve faster adaptation and larger progress rates compared to the CSA.
However, it is shown how self-adaptation affects the progress rate levels
negatively. Furthermore, differences regarding the adaptation and stability of
$\sigma$SA with log-normal and normal mutation sampling are elaborated.