private void Awake()
{
car = GetComponent <CarControllerV2>();
startPosition = transform.position;
startRotation = transform.rotation.eulerAngles;
network = new NNet();
network.Initialize(neurons, layers);
}
private void Crossover(NNet[] newPopulation)
{
for (int i = 0; i < numberToCrossover; i += 2)
{
// These are indexes of the parents.
int indexA = i;
int indexB = i + 1;
if (genePool.Count >= 1)
{
// We need to ensure that these are not the same.
// Because if two parents are the same, we're not gonna get a new child.
indexA = genePool[Random.Range(0, genePool.Count)];
do
{
indexB = genePool[Random.Range(0, genePool.Count)];
}while (indexA == indexB);
}
NNet child1 = new NNet();
NNet child2 = new NNet();
child1.Initialize(carBrain.layers, carBrain.neurons);
child2.Initialize(carBrain.layers, carBrain.neurons);
child1.fitness = 0;
child2.fitness = 0;
for (int w = 0; w < child1.weights.Count; w++)
{
if (Random.Range(0f, 1f) < 0.5f)
{
child1.weights[w] = population[indexA].weights[w];
child2.weights[w] = population[indexB].weights[w];
}
else
{
child1.weights[w] = population[indexB].weights[w];
child2.weights[w] = population[indexA].weights[w];
}
}
for (int b = 0; b < child1.biases.Count; b++)
{
if (Random.Range(0f, 1f) < 0.5f)
{
child1.biases[b] = population[indexA].biases[b];
child2.biases[b] = population[indexB].biases[b];
}
else
{
child1.biases[b] = population[indexB].biases[b];
child2.biases[b] = population[indexA].biases[b];
}
}
newPopulation[naturallySelected] = child1;
naturallySelected++;
newPopulation[naturallySelected] = child2;
naturallySelected++;
}
}