public void Add(Genome genome)
{
Genomes.Add(genome);
}
private static ConnectionGene GetGeneFromFitterParent(NeatEvaluator evaluator, Genome fitParent, bool fitnessEqual, ConnectionGene connection, Genome genome)
{
ConnectionGene geneToTake = null;
if (fitnessEqual)
{
if (evaluator.GetRandomFloat() < 0.5)
{
geneToTake = connection.Copy(null);
}
}
else
{
if (genome == fitParent)
{
geneToTake = connection.Copy(null);
}
}
return(geneToTake);
}
public Dictionary <Genome, Species> Selection(int population)
{
if (SpeciesItems.Count == 0)
{
throw new InvalidOperationException("No species found!?");
}
Dictionary <Genome, Species> nextGeneration = new Dictionary <Genome, Species>();
float sumOfAllAdjustedFitnesses = SpeciesItems.Sum(x => x.CalcuateAdjustedFitnessSum());
var speciesByFitness = SpeciesItems.OrderByDescending(x => x.AdjustedFitnessSum).ToList();
int rank = 1;
float totalSum = sumOfAllAdjustedFitnesses;
int offspringToDistribute = population;
foreach (var species in speciesByFitness)
{
species.SetRank(rank);
rank++;
var fitnessSum = species.AdjustedFitnessSum;
float offspringPerSpecies = fitnessSum / totalSum;
totalSum -= fitnessSum;
int offspring = (int)Math.Ceiling(offspringToDistribute * offspringPerSpecies);
if (offspring > offspringToDistribute)
{
offspring = offspringToDistribute;
}
int offspringToUse = offspring;
int offspringAssigned = 0;
var champ = species.Champion.Copy();
if (champ != null && species.Genomes.Count > Evaluator.NeatConfig.ChampCopyThreshold)
{
nextGeneration.Add(champ, species);
offspringAssigned++;
offspringToUse--;
}
if (Evaluator.NeatConfig.UseStagnation)
{
float stagnationEqualTolerance = 0.001f;
float difference = species.AdjustedFitnessSum - species.LastFitness;
if (difference < stagnationEqualTolerance)
{
species.StagnationCounter++;
if (species.StagnationCounter > Evaluator.NeatConfig.StagnationThreshold)
{
offspringToUse = 0;
species.Stagnated = true;
}
}
else
{
species.StagnationCounter = 0;
}
}
species.LastFitness = species.AdjustedFitnessSum;
if (offspringToUse <= 0)
{
continue; // skip this species, because it received no population at all
}
int offspringToMate = (int)Math.Floor(offspringToUse * Evaluator.NeatConfig.CrossoverOffspringRate);
int offspringToClone = offspringToUse - offspringToMate;
var selection = species.Selection();
var adjustedFitnessGenomesLookup = selection.ToDictionary(x => x, x => (x.Fitness / species.Genomes.Count));
for (int i = 0; i < offspringToMate; i++)
{
// only mate interspecies if the rate matches and
var doInterspeciesCrossover =
speciesByFitness.Count > 1 && Evaluator.GetRandomFloat() < Evaluator.NeatConfig.InterspeciesMatingRate;
if (doInterspeciesCrossover)
{
var p1 = GetRandomGenomeBiasedAdjustedFitness(adjustedFitnessGenomesLookup);
var intermateSpeciesList = speciesByFitness.Where(x => x != species).ToList();
var intermateSpeciesRndIndex = Evaluator.Random.Next(0, intermateSpeciesList.Count);
var intermateSpecies = intermateSpeciesList[intermateSpeciesRndIndex];
if (intermateSpecies.Genomes.Count > 0)
{
var intermateGenomeIndex = Evaluator.Random.Next(0, intermateSpecies.Genomes.Count);
var intermateGenome = intermateSpecies.Genomes.Items[intermateGenomeIndex];
var child = Genome.Crossover(Evaluator, p1, intermateGenome);
child.Mutate();
nextGeneration.Add(child, species);
offspringAssigned++;
}
else
{
doInterspeciesCrossover = false; // fallback when somehow there were no genomes in the other species
}
}
if (!doInterspeciesCrossover)
{
var p1 = GetRandomGenomeBiasedAdjustedFitness(adjustedFitnessGenomesLookup);
var p2 = GetRandomGenomeBiasedAdjustedFitness(adjustedFitnessGenomesLookup);
var child = Genome.Crossover(Evaluator, p1, p2);
child.Mutate();
nextGeneration.Add(child, species);
offspringAssigned++;
}
}
for (int i = 0; i < offspringToClone; i++)
{
var p1 = GetRandomGenomeBiasedAdjustedFitness(adjustedFitnessGenomesLookup);
var clone = p1.Copy();
clone.Mutate();
nextGeneration.Add(clone, species);
offspringAssigned++;
}
offspringToDistribute -= offspringAssigned;
}
return(nextGeneration);
}