/// <summary>
/// Get Genomes Fitness
/// </summary>
private void GetGenomesFitness()
{
foreach (Genome genome in _genomes)
{
// Get Species of the Genome
Species species = _genomesSpecies[genome];
float fitness = EvaluateGenome(genome);
float adjustedFitness = fitness / _genomesSpecies[genome].Genomes.Count;
species.AddAdjustedFitness(adjustedFitness);
genome.Fitness = adjustedFitness;
species.Genomes.Add(new Genome(genome));
if (fitness > BestFitness)
{
BestFitness = fitness;
BestGenome = genome;
}
}
}
// Runs one generation
public void Evaluate()
{
// Reset everything for next generation
foreach (Species s in species)
{
s.Reset(random);
}
fitnessMap.Clear();
speciesMap.Clear();
nextGenGenomes.Clear();
highestFitness = float.MinValue;
fittestGenome = null;
// Place genomes into species
foreach (Genome g in genomes)
{
bool foundSpecies = false;
foreach (Species s in species)
{
if (Genome.CompatibilityDistance(g, s.mascot, C1, C2, C3) < DT)
{ // compatibility distance is less than DT, so genome belongs to this species
s.members.Add(g);
speciesMap[g] = s;
foundSpecies = true;
break;
}
}
if (!foundSpecies)
{ // if there is no appropiate species for genome, make a new one
Species newSpecies = new Species(g);
species.Add(newSpecies);
speciesMap[g] = newSpecies;
}
}
// Remove unused species
foreach (Species s in species)
{
if (!s.members.Any())
{
species.Remove(s);
}
}
// Evaluate genomes and assign score
foreach (Genome g in genomes)
{
Species s = speciesMap[g]; // Get species of the genome
float score = evaluateGenome(g); // fitness of Genome
float adjustedScore = score / speciesMap[g].members.Count;
s.AddAdjustedFitness(adjustedScore);
s.fitnessPop.Add(new FitnessGenome(g, adjustedScore));
fitnessMap[g] = adjustedScore;
if (score > highestFitness)
{
highestFitness = score;
fittestGenome = g;
}
}
// put best genome from each species into next generation
// species = species.OrderByDescending(s => s.fitnessPop).ToList();
foreach (Species s in species)
{
FitnessGenome fittestInSpecies = s.fitnessPop.Max();
nextGenGenomes.Add(fittestInSpecies.genome);
}
// Breed the rest of the genomes
while (nextGenGenomes.Count < populationSize)
{ // replace removed genomes by randomly breeding
Species s = getRandomSpeciesBiasedAjdustedFitness(random);
Genome p1 = getRandomGenomeBiasedAdjustedFitness(s, random);
Genome p2 = getRandomGenomeBiasedAdjustedFitness(s, random);
Genome child = new Genome();
if (fitnessMap[p1] >= fitnessMap[p2])
{
child.Crossover(p1, p2);
}
else
{
child.Crossover(p2, p1);
}
if (Random.Range(0f, 1f) < MUTATION_RATE)
{
child.Mutation();
}
if (Random.Range(0f, 1f) < ADD_CONNECTION_RATE)
{
//Debug.Log("Adding connection mutation...");
child.AddConnectionMutation(connectionInnovation, 10);
}
if (Random.Range(0f, 1f) < ADD_NODE_RATE)
{
//Debug.Log("Adding node mutation...");
child.AddNodeMutation(connectionInnovation, nodeInnovation);
}
nextGenGenomes.Add(child);
}
genomes = nextGenGenomes;
nextGenGenomes = new List <Genome>();
}