/**
* Add a synapse between two random neurons
* not currently connected
* add a random weight to the synapse
*/
private void addNewSynapse()
{
List <ZeroSynapse> currentSynapses = this.genome.getAllSynapses();
int attempts = 0;
ZeroSynapse possibleSynapse = null;
do
{
if (attempts++ > 40)
{
return;
}
int from = genome.getNeurons(true, true, false)[RandomUtil.integer(0, this.genome.getNeurons(true, true, false).Count - 1)];
List <int> leftOver = this.genome.getNeurons(false, true, true);
if (leftOver.Count == 0)
{
continue;
}
int to = leftOver[RandomUtil.integer(0, leftOver.Count - 1)];
possibleSynapse = new ZeroSynapse(from, to);
} while (((possibleSynapse == null) || ((possibleSynapse.from == possibleSynapse.to) || (currentSynapses.Contains(possibleSynapse) || isRecurrent(possibleSynapse)))));
genome.addSynapse(new Synapse(genome.neat.getNextInnovationNumber(), possibleSynapse.from, possibleSynapse.to, RandomUtil.integer(-1, 1), true), null, null);
}
// REF: [GITHUB] SanderGielisse logic for looping
// and testing unconnected neurons
// (https://github.com/SanderGielisse/Mythan)
private bool isRecurrent(ZeroSynapse with)
{
Genome tmpGenome = this.genome.clone();
if ((with != null))
{
Synapse synapse = new Synapse((tmpGenome.getHighestInnovationNumber() + 1), with.from, with.to, 0, true);
tmpGenome.addSynapse(synapse, null, null);
}
bool recc = false;
foreach (int hiddenNeuron in tmpGenome.getHiddenNeurons())
{
if (this.isRecurrent(new List <int>(), ref tmpGenome, hiddenNeuron))
{
recc = true;
}
}
return(recc);
}
