/// <summary>
/// Constructor (Crossover two genome)
/// </summary>
/// <param name="genome1"></param>
/// <param name="genome2"></param>
public Genome(Genome genome1, Genome genome2)
{
this._ea = genome1._ea;
this._pool = genome1._pool;
if (genome2._fitness > genome1._fitness)
{
Genome temp = genome1;
genome1 = genome2;
genome2 = temp;
}
Gene[] innovations = new Gene[this._ea.Pool.Innovation];
foreach (Gene g2 in genome2._genes)
{
innovations[g2.Innovation] = g2;
}
foreach (Gene g1 in genome1._genes)
{
Gene g2 = innovations[g1.Innovation];
if (g2 != null && g2.Enable && this._ea.Random.Next(0, 2) == 1)
{
this._genes.Add(new Gene(g2));
}
else
{
this._genes.Add(new Gene(g1));
}
}
this._maxNeuron = Math.Max(genome1._maxNeuron, genome2._maxNeuron);
this._connectionsMutationChance = genome1._connectionsMutationChance;
this._linkMutationChance = genome1._linkMutationChance;
this._biasMutationChance = genome1._biasMutationChance;
this._nodeMutationChance = genome1._nodeMutationChance;
this._enableMutationChance = genome1._enableMutationChance;
this._disableMutationChance = genome1._disableMutationChance;
}
/// <summary>
/// Get weights of two genome
/// </summary>
/// <param name="genome1"></param>
/// <param name="genome2"></param>
/// <returns></returns>
private double GetWeights(Genome genome1, Genome genome2)
{
double sum = 0;
int coincident = 0;
Gene[] genes = new Gene[this._ea.Pool.Innovation];
foreach (Gene gene in genome2.Genes)
{
genes[gene.Innovation] = gene;
}
foreach (Gene gene in genome1.Genes)
{
if (genes[gene.Innovation] != null)
{
sum += Math.Abs(gene.Weight - genes[gene.Innovation].Weight);
coincident++;
}
}
return(coincident == 0 ? 0 : sum / coincident);
}
/// <summary>
/// Node mutate
/// </summary>
private void NodeMutate()
{
if (this._genes.Count == 0)
{
return;
}
//int maxNode = this._network.Neurons.Count - this._ea.Outputs;
this._maxNeuron++;
//Neuron neuron = new Neuron(this._ea, ++maxNode);
//this._network.Neurons.Add(maxNode, neuron);
Gene cGene = null;
Gene nGene = null;
cGene = this._genes[this._ea.Random.Next(0, this._genes.Count - 1)];
if (!cGene.Enable)
{
return;
}
cGene.Enable = false;
nGene = new Gene(cGene);
nGene.Out = this._maxNeuron;
nGene.Weight = 1.0d;
nGene.Innovation = this._pool.GetNextInnovation();
nGene.Enable = true;
this._genes.Add(nGene);
nGene = new Gene(cGene);
nGene.Into = this._maxNeuron;
nGene.Weight = 1.0d;
nGene.Innovation = this._pool.GetNextInnovation();
nGene.Enable = true;
this._genes.Add(nGene);
}
