public Genome(NeatManager neat, Species species, int[] inputNeurons, int[] outputNeurons)
{
this.instanceID = Guid.NewGuid();
this.neat = neat;
this.species = species;
foreach (int inNeuron in inputNeurons)
{
this.addInputNeuron(inNeuron);
}
foreach (int outNeuron in outputNeurons)
{
this.addOutputNeuron(outNeuron);
}
}
private void btnTrain_Click(object sender, EventArgs e)
{
btnTrain.Text = "Training";
btnTrain.Enabled = false;
btnPlay.Enabled = false;
cbFeedback.Enabled = false;
if (_chartForm != null)
{
_chartForm.Hide();
_chartForm.Dispose();
}
InfoManager.clear();
_neat = new NeatManager(_game, (int)nGenerations.Value);
btnTrain.Text = "Train";
btnTrain.Enabled = true;
btnPlay.Enabled = true;
cbFeedback.Enabled = true;
}
public static Genome cross(NeatManager neat, Genome a, Genome b)
{
double aFitness = a.fitness;
double bFitness = b.fitness;
Genome strongest;
Genome weakest;
if (aFitness > bFitness)
{
strongest = a;
weakest = b;
}
else
{
strongest = b;
weakest = a;
}
return(crossDominant(neat, strongest, weakest));
}
private static Genome crossDominant(NeatManager neat, Genome dominant, Genome other)
{
if (dominant.synapses.Count == 0 || other.synapses.Count == 0)
{
return(null);
}
int similarityNeurons = -1;
for (int i = 1; i < 100000; i++)
{
if (dominant.hasSynapse(i) && other.hasSynapse(i))
{
similarityNeurons = i;
}
}
if (similarityNeurons == -1)
{
throw new Exception("No similarity between Genomes");
}
Genome newGenome = new Genome(neat, null, dominant.inputNeurons.ToArray(), dominant.outputNeurons.ToArray());
for (int i = 1; i <= dominant.getHighestInnovationNumber(); i++)
{
if (dominant.hasSynapse(i))
{
int innovationNumber, inputNeuron, outputNeuron;
double weigth;
bool enabled;
if (other.hasSynapse(i))
{
Random r = new Random();
if (r.Next(0, 1) == 1)
{
innovationNumber = dominant.synapses[i].innovationNumber;
inputNeuron = dominant.synapses[i].from;
outputNeuron = dominant.synapses[i].to;
weigth = dominant.synapses[i].weight;
enabled = dominant.synapses[i].enabled;
}
else
{
innovationNumber = other.synapses[i].innovationNumber;
inputNeuron = other.synapses[i].from;
outputNeuron = other.synapses[i].to;
weigth = other.synapses[i].weight;
enabled = other.synapses[i].enabled;
}
}
else
{
innovationNumber = dominant.synapses[i].innovationNumber;
inputNeuron = dominant.synapses[i].from;
outputNeuron = dominant.synapses[i].to;
weigth = dominant.synapses[i].weight;
enabled = dominant.synapses[i].enabled;
}
newGenome.addSynapse(new Synapse(innovationNumber, inputNeuron, outputNeuron, weigth, enabled), dominant, other);
}
}
newGenome.removeDuplicateSynapses();
newGenome.mutate();
return(newGenome);
}
public Population(NeatManager neat)
{
this.neat = neat;
}
