public virtual GeneModule CrossoverModule(GeneModule g2, CrossoverFunction crossoverFunction)
{
var child = GetNewThis();
crossoverFunction.Crossover(geneList, g2.geneList, child.geneList);
child.GenesHasChanged();
return(child);
}
public override GeneModule CrossoverModule(GeneModule g2, CrossoverFunction crossoverFunction)
{
var child = (DefaultSigmoid)GetNewThis();
DefaultSigmoid s2 = (DefaultSigmoid)g2;
crossoverFunction.Crossover(geneList, s2.geneList, child.geneList);
child.GenesHasChanged();
return(child);
}
public override void Load(BinaryReader r, uint id)
{
base.Load(r, id);
IsFirstGeneration = r.ReadBoolean();
Parent1 = r.ReadUInt32();
Parent2 = r.ReadUInt32();
LoadListInfo(BodyGenes, r);
LoadListInfo(MutationGenes, r);
NetChromosome = ReadNullableObject <INeuralNetChromosome>(r);
CrossoverFunction = ReadNullableObject <CrossoverFunction>(r);
}
public override INeuralNetChromosome CrossoverWith(INeuralNetChromosome netC2, CrossoverFunction crossoverFunction)
{
var c2 = (SpikeNetChromosome)netC2;
var child = new SpikeNetChromosome();
//CrossoverTwoGeneLists(MutationGenes, c2.MutationGenes, CrossoverRate.Value, child.MutationGenes);
//CrossoverTwoGeneLists(EyeRNeuronGenes, c2.EyeRNeuronGenes, CrossoverRate.Value, child.EyeRNeuronGenes);
//CrossoverTwoGeneLists(EyeGNeuronGenes, c2.EyeGNeuronGenes, CrossoverRate.Value, child.EyeGNeuronGenes);
//CrossoverTwoGeneLists(EyeBNeuronGenes, c2.EyeBNeuronGenes, CrossoverRate.Value, child.EyeBNeuronGenes);
//CrossoverTwoGeneLists(DistanceNeuronGenes, c2.DistanceNeuronGenes, CrossoverRate.Value, child.DistanceNeuronGenes);
//CrossoverTwoGeneLists(HiddenNeuronGenes, c2.HiddenNeuronGenes, CrossoverRate.Value, child.HiddenNeuronGenes);
//CrossoverTwoGeneLists(InputNeuronGenes, c2.InputNeuronGenes, CrossoverRate.Value, child.InputNeuronGenes);
//CrossoverTwoGeneLists(OutputNeuronGenes, c2.OutputNeuronGenes, CrossoverRate.Value, child.OutputNeuronGenes);
return((INeuralNetChromosome)child);
}
public static void Crossover(this CrossoverFunction crossoverFunction, NeuralNetwork child,
GenerationEvaluation evaluation, SelectionFunction selectionFunction, float fitnessPower)
{
var(b, w) = evaluation.pool.Select(selectionFunction, fitnessPower);
var(better, worse) = (b.Genes, w.Genes);
var genes = child.genes;
var count = genes.Length;
var halfCount = genes.Length / 2;
switch (crossoverFunction)
{
case CrossoverFunction.HalfWorstBest:
for (var i = 0; i < halfCount; i++)
{
child.genes[i] = better[i];
}
for (var i = halfCount; i < count; i++)
{
child.genes[i] = worse[i];
}
break;
case CrossoverFunction.HalfBestWorse:
for (var i = 0; i < halfCount; i++)
{
child.genes[i] = worse[i];
}
for (var i = halfCount; i < count; i++)
{
child.genes[i] = better[i];
}
break;
case CrossoverFunction.HalfRandomShift:
var shift = Random.Range(0, count - 1);
var overlaps = shift + halfCount > count - 1;
for (var i = 0; i < count; i++)
{
child.genes[i] = (!overlaps && i > shift && i < shift + halfCount || overlaps && !(i > shift && i < shift + halfCount) ? better : worse)[i];
}
break;
case CrossoverFunction.Step:
for (var i = 0; i < count; i++)
{
genes[i] = (i % 2 == 0 ? better : worse)[i];
}
break;
case CrossoverFunction.StepRandom:
for (var i = 0; i < count; i++)
{
genes[i] = (Random.value > .5f ? better : worse)[i];
}
break;
case CrossoverFunction.FractionRandom: {
for (var i = 0; i < count; i++)
{
var fraction = Random.value;
genes[i] = better[i] * fraction + worse[i] * (1f - fraction);
}
break;
}
case CrossoverFunction.FractionByFitness: {
var fraction = b.Fitness / (b.Fitness + w.Fitness);
for (var i = 0; i < count; i++)
{
genes[i] = better[i] * fraction + worse[i] * (1f - fraction);
}
break;
}
case CrossoverFunction.Average:
default:
for (var i = 0; i < count; i++)
{
genes[i] = (better[i] + worse[i]) * .5f;
}
break;
}
}
public abstract INeuralNetChromosome CrossoverWith(INeuralNetChromosome c2, CrossoverFunction crossoverFunction);
public override INeuralNetChromosome CrossoverWith(INeuralNetChromosome netC2, CrossoverFunction crossoverFunction)
{
var c2 = (RMP_Chromosome)netC2;
var child = new RMP_Chromosome();
crossoverFunction.Crossover(MutationGenes, c2.MutationGenes, child.MutationGenes);
crossoverFunction.Crossover(EyeRNeuronGenes, c2.EyeRNeuronGenes, child.EyeRNeuronGenes);
crossoverFunction.Crossover(EyeGNeuronGenes, c2.EyeGNeuronGenes, child.EyeGNeuronGenes);
crossoverFunction.Crossover(EyeBNeuronGenes, c2.EyeBNeuronGenes, child.EyeBNeuronGenes);
crossoverFunction.Crossover(DistanceNeuronGenes, c2.DistanceNeuronGenes, child.DistanceNeuronGenes);
crossoverFunction.Crossover(HiddenNeuronGenes, c2.HiddenNeuronGenes, child.HiddenNeuronGenes);
crossoverFunction.Crossover(InputNeuronGenes, c2.InputNeuronGenes, child.InputNeuronGenes);
crossoverFunction.Crossover(OutputNeuronGenes, c2.OutputNeuronGenes, child.OutputNeuronGenes);
child.GlobalSigmoidFunction = (SigmoidFunction)GlobalSigmoidFunction.CrossoverModule(c2.GlobalSigmoidFunction, crossoverFunction);
child.GlobalOutputSigmoidFunction = (SigmoidFunction)GlobalOutputSigmoidFunction.CrossoverModule(c2.GlobalOutputSigmoidFunction, crossoverFunction);
return(child);
}
