CMAES

CMA-ES (Covariance Matrix Adaptation Evolution Strategy) is a stochastic, derivative-free methods for numerical optimization of non-linear or non-convex continuous optimization problems. More...

Classes
class	edoEstimatorNormalAdaptive< EOT, D >
	An estimator that works on adaptive normal distributions, basically the heart of the CMA-ES algorithm. More...
class	edoNormalAdaptive< EOT >
	A normal distribution that can be updated via several components. More...
class	edoSamplerNormalAdaptive< EOT, D >
	Sample points in a multi-normal law defined by a mean vector, a covariance matrix, a sigma scale factor and evolution paths. More...

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Detailed Description

CMA-ES (Covariance Matrix Adaptation Evolution Strategy) is a stochastic, derivative-free methods for numerical optimization of non-linear or non-convex continuous optimization problems.