public override void InitPopulation()
{
maxNumberOfEvaluations = Mathf.Min(maxNumberOfEvaluations, populationSize);
populationRed = new List <Individual> ();
populationBlue = new List <Individual>();
while (populationRed.Count < populationSize)
{
HillClimberIndividual new_ind_red = new HillClimberIndividual(NNTopology, maxNumberOfEvaluations, mutationMethod);
HillClimberIndividual new_ind_blue = new HillClimberIndividual(NNTopology, maxNumberOfEvaluations, mutationMethod);
if (seedPopulationFromFile)
{
NeuralNetwork nnRed = getRedIndividualFromFile();
NeuralNetwork nnBlue = getBlueIndividualFromFile();
new_ind_red.Initialize(nnRed);
new_ind_blue.Initialize(nnBlue);
//only the first individual is an exact copy. the other are going to suffer mutations
if (populationRed.Count != 0 && populationBlue.Count != 0)
{
new_ind_red.Mutate(mutationProbabilityRedPopulation);
new_ind_blue.Mutate(mutationProbabilityBluePopulation);
}
}
else
{
new_ind_red.Initialize();
new_ind_blue.Initialize();
}
populationRed.Add(new_ind_red);
populationBlue.Add(new_ind_blue);
}
}
//The Step function assumes that the fitness values of all the individuals in the population have been calculated.
public override void Step()
{
List <Individual> new_pop = new List <Individual> ();
updateReport(); //called to get some stats
// fills the rest with mutations of the best !
for (int i = 0; i < populationSize; i++)
{
HillClimberIndividual tmp = (HillClimberIndividual)overallBest.Clone();
tmp.Mutate(mutationProbability);
new_pop.Add(tmp.Clone());
}
population = new_pop;
generation++;
}
//The Step function assumes that the fitness values of all the individuals in the population have been calculated.
public override void Step()
{
List<Individual> newPopRed = new List<Individual> ();
List<Individual> newPopBlue = new List<Individual>();
updateReport (); //called to get some stats
// fills the rest with mutations of the best !
for (int i = 0; i < populationSize ; i++) {
HillClimberIndividual tmpRed = (HillClimberIndividual) overallBestRed.Clone ();
HillClimberIndividual tmpBlue = (HillClimberIndividual) overallBestBlue.Clone();
tmpRed.Mutate (mutationProbabilityRedPopulation);
tmpBlue.Mutate(mutationProbabilityBluePopulation);
newPopRed.Add (tmpRed.Clone());
newPopBlue.Add(tmpBlue.Clone());
}
populationRed = newPopRed;
populationBlue = newPopBlue;
generation++;
}