protected void InitGeneticManager()
{
var initialGenerationGenerator = new NeuralInitialGenerationCreatorBase(
InitNeuralModel(),
new RecursiveNetworkOpBaker());
var selection = new RouletteWheelSelectionWithRepetion();
var crossover = new OnePointCrossover(true);
var breeding = new BreedingClassic(
crossoverPart,
minProduction: 1,
selection: selection,
crossover: crossover,
mutationManager: InitMutations()
);
var reinsertion = new ReinsertionFromSelection(
reinsertionPart,
minProduction: 0,
selection: new EliteSelection());
var producers = new IGenomeProducer[] { breeding, reinsertion };
var genomeForge = new GenomeForge(producers);
var generationManager = new GenerationManagerKeepLast();
geneticManager = new GeneticManagerClassic(
generationManager,
initialGenerationGenerator,
genomeForge,
genomesCount
);
geneticManager.Init();
}
public Program()
{
var synapseTracker = new SynapseInnovNbTracker();
var initialGenerationGenerator = new NeuralInitialGenerationCreatorBase(
InitModel(),
new RecursiveNetworkOpBaker());
//var selection = new EliteSelection();
var selection = new RouletteWheelSelectionWithRepetion();
var crossover = new OnePointCrossover(true);
var breeding = new BreedingClassic(
crossoverPart,
1,
selection,
crossover,
InitMutations()
);
var reinsertion = new ReinsertionFromSelection(
reinsertionPart, 0, new EliteSelection());
var producers = new IGenomeProducer[] { breeding, reinsertion };
var genomeForge = new GenomeForge(producers);
var generationManager = new GenerationManagerKeepLast();
geneticManager = new GeneticManagerClassic(
generationManager,
initialGenerationGenerator,
genomeForge,
genomesCount
);
geneticManager.Init();
}
private void InitGenetics()
{
var initialGenerationGenerator = new NeuralInitialGenerationCreatorBase(
//Init4InputsNeuralModel(),
Init2InputsNeuralModel(),
new FeedForwardOpBaker());
//var selection = new EliteSelection();
//var selection = new RouletteWheelSelection();
var selection = new RouletteWheelSelectionWithRepetion();
var crossover = new OnePointCrossover(true);
var breeding = new BreedingClassic(
crossoverPart,
1,
selection,
crossover,
InitMutations()
);
var reinsertion = new ReinsertionFromSelection(reinsertionPart, 0, new EliteSelection());
var producers = new IGenomeProducer[] { breeding, reinsertion };
var genomeForge = new GenomeForge(producers);
var generationManager = new GenerationManagerKeepLast();
geneticManager = new GeneticManagerClassic(
generationManager,
initialGenerationGenerator,
genomeForge,
genomesCount
);
geneticManager.Init();
}
public void CheckIfAllAreSelected()
{
var selection = new RouletteWheelSelection();
var generationMng = new GenerationManagerKeepLast();
var genomes = new List <GenomeBase>(50);
for (int i = 0; i < genomes.Count; i++)
{
var newGenome = new GenomeBase
{
Fitness = i - 25
};
genomes.Add(newGenome);
}
generationMng.RegisterNewGeneration(new Generation(genomes.ToArray(), 0));
var roulette = new RouletteWheelSelection();
roulette.Prepare(generationMng.GetGenomes().ToArray(), null, null, genomes.Count);
var selected = roulette.Select(genomes.Count).ToArray();
Assert.True(selected.Count() == genomes.Count);
Assert.False(selected.Any(x => x == null));
foreach (var genome in selected)
{
Assert.True(selected.Count(x => x == genome) == 1);
}
}
public Program()
{
GARandomManager.Random = new RandomClassic((int)DateTime.Now.Ticks);
var generationManager = new GenerationManagerKeepLast();
var initialGenerationGenerator = new GASumInitialGenerationGenerator
{
GeneCount = genesCount,
MinValue = minGeneValue,
MaxValue = maxGeneValue
};
var selection = new EliteSelection();
var crossover = new OnePointCrossover(useBothChildren: true);
var breeding = new BreedingClassic(
crossoverPart,
minProduction: 1,
selection: selection,
crossover: crossover,
mutationManager: InitMutations());
var reinsertion = new ReinsertionFromSelection(
reinsertionPart,
minProduction: 1,
selection: new EliteSelection());
var producers = new List <IGenomeProducer>
{
reinsertion,
breeding
};
var genomeForge = new GenomeForge(producers);
geneticManager = new GeneticManagerClassic(
generationManager,
initialGenerationGenerator,
genomeForge,
genomesCount
);
geneticManager.Init();
fitnessEvaluation = new FitnessEvaluation();
}
public Program()
{
datasets = GenerateDatasets(25, () => GARandomManager.Random.Next(1, 20)).ToArray();
//datasets = GenerateDatasets(50, 10).ToArray();
var synapseTracker = new SynapseInnovNbTracker();
var initialGenerationGenerator = new NeuralInitialGenerationCreatorBase(
InitModel(),
new FeedForwardOpBaker());
//var selection = new EliteSelection();
var selection = new RouletteWheelSelectionWithRepetion();
var crossover = new OnePointCrossover(true);
var breeding = new BreedingClassic(
crossoverPart,
1,
selection,
crossover,
InitMutations()
);
var reinsertion = new ReinsertionFromSelection(
reinsertionPart, 0, new EliteSelection());
var producers = new IGenomeProducer[] { breeding, reinsertion };
var genomeForge = new GenomeForge(producers);
var generationManager = new GenerationManagerKeepLast();
geneticManager = new GeneticManagerClassic(
generationManager,
initialGenerationGenerator,
genomeForge,
genomesCount
);
geneticManager.Init();
}
public Salesman(Vector2[] locations)
{
Locations = locations;
var initialGenerationGenerator = new TSInitGenerationGenerator(Locations);
var selection = new RouletteWheelSelectionWithRepetion();
var crossover = new TSCrossover();
var breeding = new BreedingClassic(
crossoverPart,
0,
selection,
crossover,
InitMutations()
);
var reinsertion = new ReinsertionFromSelection(
reinsertionPart,
minProduction: 0,
selection: new EliteSelection());
var producers = new IGenomeProducer[]
{
reinsertion,
breeding
};
var genomeForge = new GenomeForge(producers);
var generationManager = new GenerationManagerKeepLast();
geneticManager = new GeneticManagerClassic(
generationManager,
initialGenerationGenerator,
genomeForge,
genomesCount
);
geneticManager.Init();
}
