public GenesisPhenotype(Counter counter, Genome genome, int inputs, int outputs)
{
for (int i = 0; i < inputs; i++)
{
Neuron n = new Neuron(new Linear(), counter.GetNeuronInnovation());
genome.AddNeuron(n);
inputNeurons.Add(n);
}
for (int i = 0; i < outputs; i++)
{
Neuron n = new Neuron(new Linear(), counter.GetNeuronInnovation());
genome.AddNeuron(n);
outputNeurons.Add(n);
}
foreach (Neuron inputN in inputNeurons)
{
foreach (Neuron outputN in outputNeurons)
{
Synapse s = new Synapse(counter.GetSynapseInnovation(), inputN.GetId, outputN.GetId, true);
genome.AddSynapse(s);
synapses.Add(s);
}
}
}
/// <summary>
/// Mates/combines 2 genomes into 2 different OffSpring Aka Crossover
/// </summary>
public void Mate(Genome Partner, Genome OffSpring1, Genome OffSpring2)
{
List <int> InovationNumbersList = GetInovationList().Union(Partner.GetInovationList()).ToList();
List <Node> ToAddNodes = new List <Node>();
foreach (int inovation in InovationNumbersList)
{
Neuron myNeuron = GetNeuron(inovation);
Neuron partnerNeuron = Partner.GetNeuron(inovation);
if (myNeuron != null && partnerNeuron != null) //Both Genomes have the selected neuron, a random one will be selected, the oposing one is added to the other OffSpring
{
if (Random.value > 0.5f) //50% chance
{
OffSpring1.AddNeuron(myNeuron, true);
OffSpring2.AddNeuron(partnerNeuron, true);
}
else
{
OffSpring1.AddNeuron(partnerNeuron, true);
OffSpring2.AddNeuron(myNeuron, true);
}
}
else if (myNeuron != null)//the neuron is not present in the Partner, it's labeled as either disjoint or excess, it will be added to both
{
OffSpring1.AddNeuron(myNeuron, true);
OffSpring2.AddNeuron(myNeuron, true);
}
else if (partnerNeuron != null)
{
OffSpring1.AddNeuron(partnerNeuron, true);
OffSpring2.AddNeuron(partnerNeuron, true);
}
}
}
// Update is called once per frame
void Update()
{
if (Input.GetMouseButtonDown(0))
{
genome.AddNeuron(1, ref innovations, 3);
network.DestroyNetwork();
network = genome.CreateNetwork();
network.VisualizeNetwork(panel.GetComponent <RectTransform>(), perceptron, link, loopLink, false);
print(genome.GetPerceptronGenes().Count);
}
if (Input.GetMouseButtonDown(1))
{
genome.AddLink(1, .5f, ref innovations, 3, 3);
network.DestroyNetwork();
network = genome.CreateNetwork();
network.VisualizeNetwork(panel.GetComponent <RectTransform>(), perceptron, link, loopLink, false);
}
}