public void AddIntermediateNode(LinkGene a)
{
a.Disabled = true;
int nid = AddNode(NodeType.Intermediate);
AddConnection(a.Source, nid, RandomWeight());
AddConnection(nid, a.Destination, RandomWeight());
}
public void AddConnection(int source, int destination, double weight)
{
var lg = new LinkGene(source, destination, weight);
LinkGenotype.Add(lg);
NodeGenotype[source].Outputs.Add(lg);
NodeGenotype[destination].Inputs.Add(lg);
}
private void AddConnection(int source, int destination, double weight, int innovation)
{
var lg = new LinkGene(source, destination, weight)
{
Innovation = innovation
};
LinkGenotype.Add(lg);
NodeGenotype[source].Outputs.Add(lg);
NodeGenotype[destination].Inputs.Add(lg);
}
public void Mutate()
{
// Add Node Mutation
if (NEATNET.Random.NextDouble() < AddNodeMutationChance)
{
// There's a possibility that there aren't any links at all
if (LinkGenotype.Count > 0)
{
// Pick random link
int ridx = NEATNET.Random.Next(LinkGenotype.Count);
LinkGene a = LinkGenotype[ridx];
// Add an intermediate node in the link
AddIntermediateNode(a);
}
}
// Add Link Mutation
if (NEATNET.Random.NextDouble() < AddLinkMutationChance)
{
// Pick two unique neurons, there are guaranteed to be at least two
// Starting neuron cannot be an output neuron, ending neuron cannot be an input neuron
// Only connect lower nodes to higher nodes (assuming input nodes are lowest, intermediate are sorted by ID, and output are highest)
// TODO Implementation is flawed, must select two nodes that are UNCONNECTED
int ridxa = NEATNET.Random.Next(NextNeuronID - OutputNodeCount);
if (ridxa >= InputNodeCount)
{
ridxa += OutputNodeCount; // skip the output nodes
}
int ridxb = NEATNET.Random.Next(OutputNodeCount + NextNeuronID - ridxa - 1);
if (ridxb >= OutputNodeCount)
{
ridxb += ridxa - OutputNodeCount + 1;
}
else
{
ridxb += InputNodeCount;
}
if (!LinkGeneExists(ridxa, ridxb))
{
AddConnection(ridxa, ridxb, RandomWeight());
}
}
// Link Weight Mutation
for (int i = 0; i < LinkGenotype.Count; i++)
{
var lg = LinkGenotype[i];
if (NEATNET.Random.NextDouble() < WeightMutationChance)
{
if (NEATNET.Random.NextDouble() < WeightPerturbChance)
{
// Perturb weighting by a uniform amount
lg.Weight += WeightPerturbEpsilon * RandomWeight();
}
else
{
// Randomize weighting
lg.Weight = RandomWeight();
}
}
}
// TODO Implement other mutation types
}
