private void ShowBasicStrategyButton_Click(object sender, RoutedEventArgs e)
{
basicStrategy = new BasicStrategy();
StrategyViewer.Draw(BasicStrategyCanvas, basicStrategy, string.Empty, null);
TestBasicStrategyButton.IsEnabled = true;
}
private void EvolveGeneticStrategyButton_Click(object sender, RoutedEventArgs e)
{
OutputTextBlock.Text = "Evolving...";
Task.Run(() =>
{
var chromosome = new BlackjackChromosome();
var fitness = new BlackjackFitness();
var population = new Population(Settings.GeneticSettings.MinPopulationSize, Settings.GeneticSettings.MaxPopulationSize, chromosome);
ISelection selection;
switch (Settings.GeneticSettings.SelectionType)
{
case SelectionType.Elite:
selection = new EliteSelection();
break;
case SelectionType.RouletteWheel:
selection = new RouletteWheelSelection();
break;
case SelectionType.StochasticUniversalSampling:
selection = new StochasticUniversalSamplingSelection();
break;
case SelectionType.Tournament:
selection = new TournamentSelection(Settings.GeneticSettings.TournamentSize);
break;
default:
throw new InvalidOperationException();
}
ICrossover crossover;
switch (Settings.GeneticSettings.CrossoverType)
{
case CrossoverType.AlternatingPosition:
crossover = new AlternatingPositionCrossover();
break;
case CrossoverType.CutAndSplice:
crossover = new CutAndSpliceCrossover();
break;
case CrossoverType.Cycle:
crossover = new CycleCrossover();
break;
case CrossoverType.OnePoint:
crossover = new OnePointCrossover();
break;
case CrossoverType.TwoPoint:
crossover = new TwoPointCrossover();
break;
case CrossoverType.OrderBased:
crossover = new OrderBasedCrossover();
break;
case CrossoverType.Ordered:
crossover = new OrderedCrossover();
break;
case CrossoverType.PartiallyMapped:
crossover = new PartiallyMappedCrossover();
break;
case CrossoverType.PositionBased:
crossover = new PositionBasedCrossover();
break;
case CrossoverType.ThreeParent:
crossover = new ThreeParentCrossover();
break;
case CrossoverType.Uniform:
crossover = new UniformCrossover(Settings.Current.GeneticSettings.MixProbability);
break;
case CrossoverType.VotingRecombination:
crossover = new VotingRecombinationCrossover();
break;
default:
throw new InvalidOperationException();
}
var mutation = new UniformMutation();
var termination = new FitnessStagnationTermination(Settings.Current.GeneticSettings.NumStagnantGenerations);
var taskExecutor = new ParallelTaskExecutor();
var ga = new GeneticAlgorithm(
population,
fitness,
selection,
crossover,
mutation);
ga.Termination = termination;
ga.TaskExecutor = taskExecutor;
ga.MutationProbability = Settings.GeneticSettings.MutationProbability;
ga.CrossoverProbability = Settings.GeneticSettings.CrossoverProbability;
var latestFitness = double.MinValue;
ga.GenerationRan += (s, o) =>
{
geneticStrategy = (IStrategy)ga.BestChromosome;
var generationNumber = ga.GenerationsNumber;
var bestFitness = ga.BestChromosome.Fitness.Value;
var avgFitness = ga.Population.CurrentGeneration.Chromosomes.Average(c => c.Fitness.Value);
Dispatcher.Invoke(() =>
{
if (generationNumber == 1)
{
OutputTextBlock.Text = string.Empty;
}
OutputTextBlock.Text = $"Gen: {generationNumber}\tFit: {bestFitness}\tAvg: {avgFitness.ToString("0")}\n" + OutputTextBlock.Text;
if (bestFitness != latestFitness)
{
latestFitness = bestFitness;
var savedImageName = Settings.Current.GeneticSettings.SaveImagePerGeneration ? "gen" + generationNumber : null;
StrategyViewer.Draw(GeneticStrategyCanvas, geneticStrategy, $"Best from generation {generationNumber}", savedImageName);
}
}, DispatcherPriority.Background);
};
ga.TerminationReached += (s, o) =>
{
Dispatcher.Invoke(() =>
{
OutputTextBlock.Text = "Termination reached.\n" + OutputTextBlock.Text;
TestGeneticStrategyButton.IsEnabled = true;
}, DispatcherPriority.Background);
};
ga.Start();
});
}
