public static void OnOffConnectionMutation(EvolveNeuroNet neuroNet)
{
List <Connection> connections = neuroNet.ToConnectionList();
int index = Random.Range(0, connections.Count);
if (connections[index].IsActive)
{
connections[index].Deactivate();
}
else
{
connections[index].Activate();
}
}
public static void WeightMutation(EvolveNeuroNet neuroNet)
{
List <Connection> connections = neuroNet.ToConnectionList();
if (connections.Count != 0)
{
int index = Random.Range(0, connections.Count);
float mutationRate = Mathf.Lerp(0.1f, 0.01f, Environment.Generation / 1000f);
float mutation = 12f * mutationRate;
if (Random.Range(0, 100) < 50)
{
connections[index].Weight += mutation;
}
else
{
connections[index].Weight -= mutation;
}
}
}
public static void AddNodeMutation(EvolveNeuroNet neuroNet)
{
List <Connection> connections = neuroNet.ToConnectionList();
if (connections.Count != 0)
{
bool found = false;
foreach (var conn in connections)
{
if (conn.IsActive)
{
found = true;
}
}
if (found)
{
int index = 0;
found = false;
do
{
index = Random.Range(0, connections.Count);
if (connections[index].IsActive)
{
found = true;
}
} while (!found);
connections[index].Deactivate();
Neuron neuron = neuroNet.AddNeuron();
neuroNet.AddConnection(connections[index].Source, neuron);
neuroNet.AddConnection(neuron, connections[index].Target);
List <Neuron> list = new List <Neuron>();
list.Add(neuron);
neuroNet.HiddenLayer.Add(list);
}
RebuildNet(neuroNet);
}
}
private static void RebuildNet(EvolveNeuroNet neuroNet)
{
List <Connection> connCopy = CopyConnections(neuroNet.ToConnectionList());
neuroNet.GenerateFromConnections(connCopy);
}