public double[] CrossOverAndMutation(double[] _weights, int _type, bool closer)
{
WeightsGenerator _wg = new WeightsGenerator();
if (closer)
{
//oldweights = _weights;
//Select some weights at random and record
List <int> weightIndexes = new List <int>();
for (int i = 0; i < _weights.Length / 5; i++)
{
weightIndexes.Add(rng.Next(_weights.Length));
}
//shift values up/down by around 2%
for (int i = 0; i < weightIndexes.Count; i++)
{
_weights[weightIndexes[i]] = _weights[weightIndexes[i]] + rng.NextDouble();
}
weightIndexes.Clear();
}
else
{
_weights = _wg.CreateWeights(3, _weights.Length);
}
//on next pass check if closer, if not go the other way, if so, repeat.
return(_weights);
}
public double[] CrossOverAndMutation(bool[] _evaluateFitnessResult, double[] _weights, int _type)
{
WeightsGenerator _wg = new WeightsGenerator();
double[] _childWeights = new double[_weights.Length];
for (int i = 0; i < _weights.Length; i++)
{
if (_evaluateFitnessResult[i])
{
_childWeights[i] = _weights[i];
}
else
{
_childWeights[i] = _wg.CreateWeights(_type, 1)[0];
}
}
return(_childWeights);
}
public double[] GeneratePopulation(int _amount, int _type)
{
WeightsGenerator _wg = new WeightsGenerator();
return(_wg.CreateWeights(_type, _amount));
}
