public void Init()
{
var innovations = new InnovationCollection();
var neuronGenes = Enumerable.Range(0, 3).Select(i => {
var inId = innovations.GetInitialNeuronInnovationId(i);
return(new NeuronGene(inId, NeuronType.HiddenNeuron));
}).ToGeneList();
var synapseGenes = Enumerable.Range(0, 3).Select(i => {
var inId = innovations.GetSynapseInnovationId(i, i + 1);
return(new SynapseGene(inId, i, i + 1, true));
}).ToGeneList();
var protoGenotype = new Genotype(neuronGenes, synapseGenes);
var phenotypes = Enumerable.Range(0, 100).Select(_ => {
var gt = Genotype.FromPrototype(protoGenotype);
var pt = new Phenotype(gt);
return(pt);
}).ToArray();
var distanceMetric = new NEAT.DistanceMetric(0.0f, 0.0f, 35.0f);
var speciation = new NEAT.Speciation(10, 50.0f, 0.2f, distanceMetric);
species = speciation.Speciate(new NEAT.Specie[0], phenotypes);
}
public void Init()
{
var innovations = new InnovationCollection();
var neuronGenes = Enumerable.Range(0, 3).Select(i => {
var inId = innovations.GetInitialNeuronInnovationId(i);
return new NeuronGene(inId, NeuronType.HiddenNeuron);
}).ToGeneList();
var synapseGenes = Enumerable.Range(0, 3).Select(i => {
var inId = innovations.GetSynapseInnovationId(i, i + 1);
return new SynapseGene(inId, i, i + 1, true);
}).ToGeneList();
var protoGenotype = new Genotype(neuronGenes, synapseGenes);
var phenotypes = Enumerable.Range(0, 100).Select(_ => {
var gt = Genotype.FromPrototype(protoGenotype);
var pt = new Phenotype(gt);
return pt;
}).ToArray();
var distanceMetric = new NEAT.DistanceMetric(0.0f, 0.0f, 35.0f);
var speciation = new NEAT.Speciation(10, 50.0f, 0.2f, distanceMetric);
species = speciation.Speciate(new NEAT.Specie[0], phenotypes);
}
public Genotype Crossover(Phenotype a, Phenotype b)
{
if (a == b)
{
return(new Genotype(a.Genotype));
}
var aGenotype = new Genotype(a.Genotype);
var bGenotype = new Genotype(b.Genotype);
var newNeuronGenes = CrossoverGenes <NeuronGene>(aGenotype.NeuronGenes, bGenotype.NeuronGenes, a.AdjustedFitness, b.AdjustedFitness);
var newSynapseGenes = CrossoverGenes <SynapseGene>(aGenotype.SynapseGenes, bGenotype.SynapseGenes, a.AdjustedFitness, b.AdjustedFitness);
return(new Genotype(newNeuronGenes, newSynapseGenes));
}
public void TestSpecie()
{
var specie = new Specie(13, protoGenotype, 0, 0, 0.0f);
for (int i = 0; i < 100; i++) {
var gt = Genotype.FromPrototype(protoGenotype);
var pt = new Phenotype(gt);
specie.Add(pt);
}
foreach (var pt in specie) {
pt.AdjustedFitness = 1.0f / (float)specie.Count;
}
Assert.AreEqual(0.0f, specie.MeanFitness, 0.001f);
Assert.AreEqual(0.01f, specie.MeanAdjustedFitness, 0.001f);
Assert.AreEqual(100, specie.Count);
}
public void TestSpecie()
{
var specie = new Specie(13, protoGenotype, 0, 0, 0.0f);
for (int i = 0; i < 100; i++)
{
var gt = Genotype.FromPrototype(protoGenotype);
var pt = new Phenotype(gt);
specie.Add(pt);
}
foreach (var pt in specie)
{
pt.AdjustedFitness = 1.0f / (float)specie.Count;
}
Assert.AreEqual(0.0f, specie.MeanFitness, 0.001f);
Assert.AreEqual(0.01f, specie.MeanAdjustedFitness, 0.001f);
Assert.AreEqual(100, specie.Count);
}
public void Init()
{
var innovations = new InnovationCollection();
var neuronGenes = Enumerable.Range(0, 3).Select(i => {
var inId = innovations.GetInitialNeuronInnovationId(i);
return new NeuronGene(inId, NeuronType.HiddenNeuron);
}).ToGeneList();
var synapseGenes = Enumerable.Range(0, 3).Select(i => {
var inId = innovations.GetSynapseInnovationId(i, i + 1);
return new SynapseGene(inId, i, i + 1, true);
}).ToGeneList();
var protoGenotype = new Genotype(neuronGenes, synapseGenes);
phenotypes = Enumerable.Range(0, 100).Select(_ => {
var gt = Genotype.FromPrototype(protoGenotype);
var pt = new Phenotype(gt);
return pt;
}).ToArray();
}
public void Init()
{
var innovations = new InnovationCollection();
var neuronGenes = Enumerable.Range(0, 3).Select(i => {
var inId = innovations.GetInitialNeuronInnovationId(i);
return(new NeuronGene(inId, NeuronType.HiddenNeuron));
}).ToGeneList();
var synapseGenes = Enumerable.Range(0, 3).Select(i => {
var inId = innovations.GetSynapseInnovationId(i, i + 1);
return(new SynapseGene(inId, i, i + 1, true));
}).ToGeneList();
var protoGenotype = new Genotype(neuronGenes, synapseGenes);
phenotypes = Enumerable.Range(0, 100).Select(_ => {
var gt = Genotype.FromPrototype(protoGenotype);
var pt = new Phenotype(gt);
return(pt);
}).ToArray();
}
public void TestMultipointCrossover()
{
var innovationIdsA = new int[]{1, 2, 3, 4, 5, 8};
var neuronGenesA = innovationIdsA.Select(i => new NeuronGene(i, NeuronType.HiddenNeuron)).ToGeneList();
var innovationIdsB = new int[]{1, 2, 3, 4, 5, 6, 7, 9, 10};
var neuronGenesB = innovationIdsB.Select(i => new NeuronGene(i, NeuronType.HiddenNeuron)).ToGeneList();
var expectedInnovationIds = new int[]{1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
var genotypeA = new Genotype(neuronGenesA, new GeneList<SynapseGene>(0));
var genotypeB = new Genotype(neuronGenesB, new GeneList<SynapseGene>(0));
var phenotypeA = new Phenotype(genotypeA);
var phenotypeB = new Phenotype(genotypeB);
var crossover = new MultipointCrossover();
var offspring = crossover.Crossover(phenotypeA, phenotypeB);
var offspringInnovationIds = offspring.NeuronGenes.Select(g =>
g.InnovationId).ToArray();
Assert.AreEqual(expectedInnovationIds, offspringInnovationIds);
}
public void TestMultipointCrossover()
{
var innovationIdsA = new int[] { 1, 2, 3, 4, 5, 8 };
var neuronGenesA = innovationIdsA.Select(i => new NeuronGene(i, NeuronType.HiddenNeuron)).ToGeneList();
var innovationIdsB = new int[] { 1, 2, 3, 4, 5, 6, 7, 9, 10 };
var neuronGenesB = innovationIdsB.Select(i => new NeuronGene(i, NeuronType.HiddenNeuron)).ToGeneList();
var expectedInnovationIds = new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };
var genotypeA = new Genotype(neuronGenesA, new GeneList <SynapseGene>(0));
var genotypeB = new Genotype(neuronGenesB, new GeneList <SynapseGene>(0));
var phenotypeA = new Phenotype(genotypeA);
var phenotypeB = new Phenotype(genotypeB);
var crossover = new MultipointCrossover();
var offspring = crossover.Crossover(phenotypeA, phenotypeB);
var offspringInnovationIds = offspring.NeuronGenes.Select(g =>
g.InnovationId).ToArray();
Assert.AreEqual(expectedInnovationIds, offspringInnovationIds);
}
