public RealGaussianMutation(List <double> sigmas, IEvaluationProfile <double> evaluationProfile, int?seed = null, double probability = 1.0)
: base(probability, evaluationProfile)
{
uniformRNG = new BoolRandom(seed);
gaussianRNG = new NormalRealRandom(seed);
this.sigmas = new List <double>(sigmas);
}
public RealGaussianMutation(double sigma, IEvaluationProfile <double> evaluationProfile, int?seed = null, double probability = 1.0)
: base(probability, evaluationProfile)
{
uniformRNG = new BoolRandom(seed);
gaussianRNG = new NormalRealRandom(seed);
sigmas = new List <double>(evaluationProfile.iSize);
for (int i = 0; i < evaluationProfile.iSize; ++i)
{
sigmas.Add(sigma);
}
}
public CMAES(IEvaluation <double> evaluation, AStopCondition stopCondition, double initSigma, int?seed = null)
: base(evaluation, stopCondition)
{
this.initSigma = initSigma;
normalRNG = new NormalRealRandom(seed);
realGenerator = new RealRandomGenerator(evaluation.pcConstraint, seed);
int N = evaluation.iSize;
previousMeans = Vector <double> .Build.Dense(N);
means = Vector <double> .Build.Dense(N);
covarianceMatrix = Matrix <double> .Build.Dense(N, N);
selectionParameters = new SelectionParameters(N);
stepSizeParameters = new StepSizeParameters(N, initSigma);
adaptationParameters = new AdaptationParameters(N, selectionParameters);
sampledPopulation = new List <Individual>(selectionParameters.Lambda);
}