/// <summary>
/// Propogate the value of the Neuron to each of the Neurons in the next layer
/// through the output Dendrites.
/// </summary>
internal void Propogate()
{
foreach (var Dendrite in OutputConnections)
{
Dendrite.Propogate();
}
}
/// <summary>
/// Add the given Dendrite to the list of output connections.
/// </summary>
/// <param name="Connection"></param>
internal void AddOutputConnection(Dendrite Connection)
{
OutputConnections.Add(Connection);
}
/// <summary>
/// Add the given Dendrite to the list of input connections.
/// </summary>
/// <param name="Connection"></param>
internal void AddInputConnection(Dendrite Connection)
{
InputConnections.Add(Connection);
}
internal static NeuralNet Breed(NeuralNet Father, NeuralNet Mother)
{
NeuralNet Child = new NeuralNet(NeuralLayerInfo);
for (UInt16 LayerIter = 0; LayerIter < NeuralLayerInfo.Count(); LayerIter += 1)
{
NeuralLayer CurrentLayer = Child.NeuralLayers[LayerIter];
for (int NeuronIter = 0; NeuronIter < CurrentLayer.NeuronsInLayer.Count(); NeuronIter += 1)
{
Neuron CurrentNeuron = CurrentLayer.NeuronsInLayer[NeuronIter];
for (int DendriteIter = 0; DendriteIter < CurrentNeuron.OutputConnections.Count(); DendriteIter += 1)
{
Dendrite CurrentDendrite = CurrentNeuron.OutputConnections[DendriteIter];
if (GlobalRandom.NextDouble() < Math.Min(MaxMutationRate, (BaseMutationRate + (MutationRateIncreasePerFailedGeneration * GensSinceLastImprv))))
{
CurrentDendrite.SetNewRandomConnectionStrength();
}
else
{
// Children are always random
switch (BreedingType)
{
case EnumBreedingType.AlwaysRandom:
CurrentDendrite.SetNewRandomConnectionStrength();
break;
// Child dendrite connection strength is the average of the mother and father
case EnumBreedingType.AverageValue:
CurrentDendrite.ConnectionStrength =
(Father.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength +
Mother.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength) / 2;
break;
// Child takes fathers or mothers dendrite connection strength
default:
case EnumBreedingType.Human:
CurrentDendrite.ConnectionStrength = (GlobalRandom.NextDouble() < 0.5)
? Father.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength
: Mother.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength;
break;
// Child dendrite connection strength pulled up and down by agreement between father and mother
case EnumBreedingType.WeightedPull:
if (Father.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength >= 0.5 &&
Mother.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength >= 0.5)
{
CurrentDendrite.ConnectionStrength = (float)Math.Min(1.0, Math.Max(
Father.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength,
Mother.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength
) + 0.01);
}
else
if (Father.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength < 0.5 &&
Mother.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength < 0.5)
{
CurrentDendrite.ConnectionStrength = (float)Math.Max(0, Math.Min(
Father.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength,
Mother.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength
) - 0.01);
}
else
{
CurrentDendrite.ConnectionStrength = (GlobalRandom.NextDouble() < 0.5)
? Father.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength
: Mother.NeuralLayers[LayerIter].NeuronsInLayer[NeuronIter].OutputConnections[DendriteIter].ConnectionStrength;
}
break;
}
}
}
}
}
return(Child);
}
