public static Genome Crossover(ref Genome mum, ref Genome dad, GeneticAlgorithm ga)
{
BestParent bestParent = GetBestParent(ref mum, ref dad);
List <int> newPerceptrons = new List <int>();
int curMum = 0;
int curDad = 0;
ConnectionGene selectedGene = null;
Genome newGenome = RecycledGenome();
while (!(curMum == mum.connections.Count && curDad == dad.connections.Count))
{
// Dad has more genes
if (curMum == mum.connections.Count && curDad != dad.connections.Count)
{
if (bestParent == BestParent.dad)
{
selectedGene = dad.GetConnectionGenes()[curDad];
}
curDad++;
if (selectedGene == null)
{
continue;
}
}
// Mum has more genes
else if (curMum != mum.connections.Count && curDad == dad.connections.Count)
{
if (bestParent == BestParent.mum)
{
selectedGene = mum.GetConnectionGenes()[curMum];
}
curMum++;
if (selectedGene == null)
{
continue;
}
}
// Mum gene innovation number is lower
else if (mum.GetConnectionGenes()[curMum].innovNum < dad.GetConnectionGenes()[curDad].innovNum)
{
if (bestParent == BestParent.mum)
{
selectedGene = mum.GetConnectionGenes()[curMum];
}
curMum++;
if (selectedGene == null)
{
continue;
}
}
// Dad gene innovation number is lower
else if (mum.GetConnectionGenes()[curMum].innovNum > dad.GetConnectionGenes()[curDad].innovNum)
{
if (bestParent == BestParent.dad)
{
selectedGene = dad.GetConnectionGenes()[curDad];
}
curDad++;
if (selectedGene == null)
{
continue;
}
}
// Both innovation numbers are equal
else if (mum.GetConnectionGenes()[curMum].innovNum == dad.GetConnectionGenes()[curDad].innovNum)
{
if (Random.Range(0f, 1f) > 0.5f)
{
selectedGene = mum.GetConnectionGenes()[curMum];
}
else
{
selectedGene = dad.GetConnectionGenes()[curDad];
}
curDad++;
curMum++;
}
else
{
Debug.Log("wtf");
}
if (selectedGene == null)
{
Debug.Log("Weird");
continue;
}
if (newGenome.connectionGeneIndex == 0)
{
newGenome.AddConnectionGeneGene(new ConnectionGene(selectedGene));
}
else
{
if (newGenome.connections[newGenome.connectionGeneIndex - 1].innovNum != selectedGene.innovNum)
{
newGenome.AddConnectionGeneGene(new ConnectionGene(selectedGene));
}
}
newPerceptrons = AddPercepID(selectedGene.from, newPerceptrons);
newPerceptrons = AddPercepID(selectedGene.to, newPerceptrons);
}
newPerceptrons.Sort();
for (int i = 0; i < GA_Parameters.inputs + 1; i++)
{
newGenome = ga.innovations.CreateNeuronFromID(i, newGenome);
}
for (int i = 0; i < GA_Parameters.outputs; i++)
{
newGenome = ga.innovations.CreateNeuronFromID(GA_Parameters.inputs + 1 + i, newGenome);
}
for (int i = 0; i < newPerceptrons.Count; i++)
{
newGenome = ga.innovations.CreateNeuronFromID(newPerceptrons[i], newGenome);
}
MutParameters mutPar = new MutParameters(mum, dad);
newGenome.ID = ga.nextGenomeID;
newGenome.inputs = mum.inputs;
newGenome.outputs = mum.outputs;
newGenome.mutPar = mutPar;
ga.nextGenomeID++;
newGenome.FinishGenome();
return(newGenome);
}