Completely Derandomized Self-Adaptation in Evolution Strategies¶
Hansen, N., & Ostermeier, A. (2001). Completely Derandomized Self-Adaptation in Evolution Strategies. Evolutionary Computation, 159-195.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Variance Bounds Selection Response
- Evolution strategies such as CMA-ES tie convergence rate to the covariance of sampled candidates; directed-evolution biotech ties the improvement rate of a designed protein to library diversity; and A/B-testing programmes find their improvement rate set by the variance of the variant population, so that low-variance programmes plateau.
This sourceCMA-ES ties convergence rate to the covariance of sampled candidates.
Supported in partVerified against the publisher's abstract
The abstract introduces covariance matrix adaptation and reports large speed-ups on badly scaled functions, but never states that convergence rate is set by the covariance of sampled candidates.
“If this objective is pursued rigor-ously, a completely derandomized self-adaptation scheme results, which adapts arbitrary normal mutation distributions. This scheme, called covariance matrix adaptation (CMA), meets the previously stated demands. It can still be considerably improved by cumulation - utilizing an evolution path rather than single search steps. Simulations on various test functions reveal local and …”
- Evolution strategies such as CMA-ES tie convergence rate to the covariance of sampled candidates; directed-evolution biotech ties the improvement rate of a designed protein to library diversity; and A/B-testing programmes find their improvement rate set by the variance of the variant population, so that low-variance programmes plateau.
Verification¶
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Registry ID ref:101b61857939 · see in the full table