// Create a new generation
public void generate()
{
// Refill the population with children from the mating pool
for (int i = 0; i < population.Length; i++)
{
int a = (int)(Random.Range(0, matingPool.Count));
int b = (int)(Random.Range(0, matingPool.Count));
DNAchar partnerA = matingPool[a];
DNAchar partnerB = matingPool[b];
DNAchar child = partnerA.crossover(partnerB);
child.mutate(mutationRate);
population[i] = child;
}
generations++;
}
public Population(string p, float m, int num)
{
target = p;
mutationRate = m;
population = new DNAchar[num];
for (int i = 0; i < population.Length; i++)
{
population[i] = new DNAchar(target.Length);
}
calcFitness();
matingPool = new List <DNAchar>();
finished = false;
generations = 0;
perfectScore = 1;
}
// Crossover
public DNAchar crossover(DNAchar partner)
{
// A new child
DNAchar child = new DNAchar(genes.Length);
int midpoint = (int)(Random.Range(0, genes.Length)); // Pick a midpoint
// Half from one, half from the other
for (int i = 0; i < genes.Length; i++)
{
if (i > midpoint)
{
child.genes[i] = genes[i];
}
else
{
child.genes[i] = partner.genes[i];
}
}
return(child);
}
public void generate()
{
// Refill the population with children from the mating pool
for (int i = 0; i < population.Length; i++)
{
int a = (int)(Random.Range(0, matingPool.Count));
int b = (int)(Random.Range(0, matingPool.Count));
//exercise9.4 two unique 'parents'
if (a == b)
{
b = b + (b > 0.5 * matingPool.Count ? -1 : 1);
}
DNAchar partnerA = matingPool[a];
DNAchar partnerB = matingPool[b];
DNAchar child = partnerA.crossover(partnerB);
child.mutate(mutationRate);
population[i] = child;
}
generations++;
}
