public Phenotype[] ChooseBestByRoulete(int qty)
{
Phenotype[] result = new Phenotype[qty];
float totalFitness = 0;
foreach (Phenotype phenotype in phenotypes)
{
totalFitness += phenotype.fitness;
}
KeyValuePair<Phenotype, double>[] candiates = new KeyValuePair<Phenotype, double>[phenotypes.Count];
int i = 0;
foreach (Phenotype phenotype in phenotypes)
{
double p = (rouleteBiasToTheBest + rnd.NextDouble() * (1 - rouleteBiasToTheBest)) * phenotype.fitness / totalFitness;
candiates[i] = new KeyValuePair<Phenotype, double>(phenotype, p);
i++;
}
IOrderedEnumerable<KeyValuePair<Phenotype, double>> bestCandidates = candiates.OrderByDescending(
(KeyValuePair<Phenotype, double> candidate) => candidate.Value
);
int added = 0;
foreach (KeyValuePair<Phenotype, double> candidate in bestCandidates)
{
result[added++] = candidate.Key;
if (added >= qty) break;
}
return result;
}
public float[][][] GenerateOffspring(int qty)
{
float[][][] result = new float[qty][][];
Phenotype[] parents = ChooseBestByRoulete(phenotypes.Count / 3);
for (int i = 0; i < qty; i++)
{
Phenotype parentA = parents[i % parents.Length];
Phenotype parentB = parents[UnityEngine.Random.Range(0, parents.Length)];
float[][] newGenes = parentA.genotype;
if (useCrossover)
{
newGenes = BreedFromCrossover(newGenes, parentB.genotype);
}
if (mutationProbability != 0)
{
applyMutation(newGenes);
}
result[i] = newGenes;
}
return(result);
}
public void AddPhenotype(float[][] genotype, float fitness)
{
Phenotype phenotype = new Phenotype() { genotype = genotype, fitness = fitness };
phenotypes.AddLast(phenotype);
if (bestPhenotype == null || bestPhenotype.fitness < phenotype.fitness) bestPhenotype = phenotype;
}
public void AddPhenotype(float[][] genotype, float fitness)
{
Phenotype phenotype = new Phenotype()
{
genotype = genotype, fitness = fitness
};
phenotypes.AddLast(phenotype);
if (bestPhenotype == null || bestPhenotype.fitness < phenotype.fitness)
{
bestPhenotype = phenotype;
}
}
public Phenotype[] ChooseBestByRoulete(int qty)
{
Phenotype[] result = new Phenotype[qty];
float totalFitness = 0;
foreach (Phenotype phenotype in phenotypes)
{
totalFitness += phenotype.fitness;
}
KeyValuePair <Phenotype, double>[] candiates = new KeyValuePair <Phenotype, double> [phenotypes.Count];
int i = 0;
foreach (Phenotype phenotype in phenotypes)
{
double p = (rouleteBiasToTheBest + rnd.NextDouble() * (1 - rouleteBiasToTheBest)) * phenotype.fitness / totalFitness;
candiates[i] = new KeyValuePair <Phenotype, double>(phenotype, p);
i++;
}
IOrderedEnumerable <KeyValuePair <Phenotype, double> > bestCandidates = candiates.OrderByDescending(
(KeyValuePair <Phenotype, double> candidate) => candidate.Value
);
int added = 0;
foreach (KeyValuePair <Phenotype, double> candidate in bestCandidates)
{
result[added++] = candidate.Key;
if (added >= qty)
{
break;
}
}
return(result);
}