private bool AreOutputs(NeatNeuron a, NeatNeuron b)
{
var aOut = false;
var bOut = false;
var outputNeurons = GetOutputNeurons();
for (var i = 0; i < outputNeurons.Count; i++)
{
var n = outputNeurons[i];
if (n == a)
{
aOut = true;
}
else if (n == b)
{
bOut = true;
}
if (aOut && bOut)
{
return(true);
}
}
return(false);
}
private bool AreConnected(NeatNeuron a, NeatNeuron b)
{
for (var i = 0; i < b.Connections.Count; i++)
{
var c = b.Connections[i];
if (!c.OutGoing && a == c.Neuron)
{
return(true);
}
}
return(false);
}
private bool CanConnect(NeatNeuron a, NeatNeuron b)
{
var same = a == b;
var canConnect = !same && !AreOutputs(a, b) && !AreConnected(a, b);
if (!_neat.Structure.AllowRecurrentConnections)
{
var isRecurrent = a.Layer > b.Layer;
canConnect = canConnect && !isRecurrent;
}
return(canConnect);
}
private void CategorizeNeuronBranchIntoLayers(NeatNeuron current, int depth = 0)
{
current.Layer = depth;
var nextLayer = current.Layer + 1;
for (var i = 0; i < current.Connections.Count; i++)
{
var c = current.Connections[i];
if (nextLayer > c.Neuron.Layer && c.OutGoing != c.Recursive)
{
CategorizeNeuronBranchIntoLayers(c.Neuron, nextLayer);
}
}
}
private void BuildFromGenes()
{
_neurons = new List <NeatNeuron>(Chromosome.NeuronCount);
for (var i = 0; i < Chromosome.NeuronCount; i++)
{
var neuron = new NeatNeuron {
Activation = _neat.Neural.ActivationFunction
};
_neurons.Add(neuron);
}
for (var i = 0; i < Chromosome.GeneCount; i++)
{
var gene = Chromosome.GetGeneAt(i);
if (gene.Enabled)
{
var inConnection = new NeatNeuron.Connection();
inConnection.Weight = gene.Weight;
inConnection.Recursive = gene.Recursive;
inConnection.Neuron = _neurons[gene.From];
_neurons[gene.To].Connections.Add(inConnection);
var outConnection = new NeatNeuron.Connection();
outConnection.Weight = gene.Weight;
outConnection.Recursive = gene.Recursive;
outConnection.Neuron = _neurons[gene.To];
outConnection.OutGoing = true;
_neurons[gene.From].Connections.Add(outConnection);
}
}
for (var i = 0; i < _neat.Structure.BiasNeuronCount; i++)
{
_neurons[i].Value = 1.0;
}
CategorizeNeuronsIntoLayers();
}
