public void Epoch()
{
PrintStats();
DestroyGameObjects();
nGeneration++;
individuals = individuals.OrderByDescending(o => o.Fitness).ToList();
List <Individual> newIndividuals = new List <Individual>();
newIndividuals.AddRange(CloneElite(ConfigManager.config.geneticAlgorithm.nElite));
newIndividuals.AddRange(ReproductionHelper.Reproduce(individuals, ConfigManager.config.geneticAlgorithm.nIndividuals - ConfigManager.config.geneticAlgorithm.nElite, GetFitness()));
MutationHelper.Mutate(newIndividuals);
enemies = new List <List <Enemy> >();
for (int i = 0; i < newIndividuals.Count; i++)
{
newIndividuals[i].Index = i;
newIndividuals[i].CreateGameObject();
enemies.Add(new List <Enemy>());
float distanceOffset = 0;
for (int j = 0; j < ConfigManager.config.nEnemies; j++)
{
enemies[i].Add(new Enemy(i, distanceOffset));
distanceOffset = enemies[i][j].Distance;
}
newIndividuals[i].SetEnemies(enemies[i]);
}
individuals = new List <Individual>(newIndividuals);
CreateGameObjects();
}
public void Epoch()
{
DestroyGameObjects();
nGeneration++;
int totalFitness = GetFitness();
individuals = individuals.OrderByDescending(o => o.fitness).ToList();
List <Individual> newIndividuals = new List <Individual>();
newIndividuals.AddRange(CloneElite(ConfigManager.config.geneticAlgorithm.nElite));
newIndividuals.AddRange(ReproductionHelper.Reproduce(individuals, ConfigManager.config.geneticAlgorithm.nIndividuals - ConfigManager.config.geneticAlgorithm.nElite, totalFitness));
MutationHelper.Mutate(newIndividuals);
for (int i = 0; i < newIndividuals.Count; i++)
{
newIndividuals[i].SetTile(tileMap.GetRandomTile());
}
PrintStats();
individuals = new List <Individual>(newIndividuals);
CreateGameObjects();
}
private static void AdvanceGeneration()
{
Individual[] nextPopulation = new Individual[Config.nIndividualsPerPopulation];
Individual[] orderedIndividuals = FitnessHelper.GetOrderedIndividuals(population);
for (int i = 0; i < Config.nElite; i++)
{
nextPopulation[i] = orderedIndividuals[i];
nextPopulation[i].wasElite = true;
}
Debug.Log("ordered generation " + generationsFinished);
Print(orderedIndividuals);
//sacar el promedio de fitness, y hacer que la mutación pase empezando por el promedio ese dividido 2 (por ejemplo, si el fitness promedio es 4, empezás a mutar desde el frame 2)
//y aumentás el mutationRate un toque
Individual[] childrenIndividuals = ReproductionHelper.GetChildrenIndividuals(population, Config.nIndividualsPerPopulation - Config.nElite);
MutationHelper.MutatePopulation(childrenIndividuals);
for (int i = Config.nElite; i < childrenIndividuals.Length + Config.nElite; i++)
{
nextPopulation[i] = childrenIndividuals[i - Config.nElite];
}
Debug.Log("next generation " + generationsFinished + 1);
Print(nextPopulation);
generationsFinished++;
individualsFinished = 0;
population = (Individual[])nextPopulation.Clone();
StartIndividual(0);
}
void Awake()
{
PhraseHelper.Init();
ReproductionHelper.Init();
MutationHelper.Init();
UIManager.Init();
PopulationManager.Init();
}
private static void AddChildren(Individual[] nextPopulation, Individual[] population)
{
Individual[] childrenIndividuals = ReproductionHelper.GetChildrenIndividuals(population, Config.nIndividualsPerPopulation - Config.nElite);
MutationHelper.MutatePopulation(childrenIndividuals);
for (int i = Config.nElite; i < childrenIndividuals.Length + Config.nElite; i++)
{
nextPopulation[i] = childrenIndividuals[i - Config.nElite];
}
}
protected override void OnNextStepClicked()
{
NumberOfSteps++;
var reproduceItems = ReproductionHelper.ReproduceReal(Function, RealItems);
var newItems =
CrossingoverHelper.MakeRealCrossingover(reproduceItems, SolutionAccuracy, CrossingoverPossibility);
MutationHelper.MutateReal(newItems, NumberOfSteps, MaxSteps, MutationPossibility);
RealItems = newItems;
var minItem = RealItems.Aggregate((i, j) =>
Function(i.X1, i.X2) < Function(j.X1, j.X2)
? i
: j);
ItemValue = $"x1: {minItem.X1}\nx2: {minItem.X2}";
var functionValue = Function(minItem.X1, minItem.X2);
MaxItemValueFunction = functionValue.ToString();
// ------------------------------------------------------
for (var i = ChartModel.Series.Count - 1; i > 0; i--)
{
ChartModel.Series.RemoveAt(i);
}
var solutions = new ScatterSeries
{
MarkerType = MarkerType.Circle,
MarkerFill = OxyColor.FromRgb(0, 0, 0xFF)
};
foreach (var p in RealItems)
{
var plotPoint = new ScatterPoint(p.X1, p.X2, 5);
solutions.Points.Add(plotPoint);
}
ChartModel.Series.Add(solutions);
var minValueSeries = new ScatterSeries
{
MarkerType = MarkerType.Circle,
MarkerFill = OxyColor.FromRgb(0xFF, 0, 0)
};
minValueSeries.Points.Add(new ScatterPoint(minItem.X1, minItem.X2, 7, functionValue));
ChartModel.Series.Add(minValueSeries);
ChartModel.InvalidatePlot(true);
}
public static void AdvanceGeneration()
{
List <Individual> newPopulation = new List <Individual>();
FitnessHelper.CalculateFitness(population);
newPopulation.AddRange(FitnessHelper.GetIndividualsWithHighestFitness(population, Config.nIndividualsToAdvanceAutomatically));
UIManager.UpdateBestPhrase(newPopulation[0].dna.phrase);
newPopulation.AddRange(ReproductionHelper.GetNewIndividuals(population, Config.nIndividuals - Config.nIndividualsToAdvanceAutomatically));
MutationHelper.MutatePopulation(population);
generationNumber++;
UIManager.UpdateGenerationNumber(generationNumber);
UIManager.UpdateFitnesses(FitnessHelper.GetFitnessInformation(population));
ReassignPopulation(newPopulation);
}
public void Epoch()
{
Debug.Log("Finished generation " + nGeneration + " with a total fitness of " + GetFitness());
PopulationHistory.AddIndividuals(Individuals);
nGeneration++;
DestroyGameObjects();
Individuals = Individuals.OrderByDescending(o => o.Fitness).ToList();
List <Individual> newIndividuals = new List <Individual>();
newIndividuals.AddRange(CloneElite(ConfigManager.config.geneticAlgorithm.nElite));
newIndividuals.AddRange(ReproductionHelper.Reproduce(Individuals, ConfigManager.config.geneticAlgorithm.nIndividuals - ConfigManager.config.geneticAlgorithm.nElite, GetFitness()));
MutationHelper.Mutate(newIndividuals.GetRange(ConfigManager.config.geneticAlgorithm.nElite, newIndividuals.Count - ConfigManager.config.geneticAlgorithm.nElite));
for (int i = 0; i < newIndividuals.Count; i++)
{
newIndividuals[i].Index = i;
}
Individuals = new List <Individual>(newIndividuals);
CreateGameObjects();
}