void SaveBestNetwork()
{
try
{
string m_Path = Application.dataPath + "/" + transform.root.gameObject.name + ".xml";
NeuralWeights neuralWeights = new NeuralWeights();
neuralWeights.bestScore = (float)bestScore;
neuralWeights.Generation = generation;
//Save this Network
if (!newNetworkVersion)
{
neuralWeights.weights = networks[0].getWeigths();
}
else
{
neuralWeights.HiddenLayers = newNetworks.HiddenLayers;
neuralWeights.InputLayer = newNetworks.InputLayer;
neuralWeights.OutputLayer = newNetworks.OutputLayer;
}
SaveWeights(m_Path, neuralWeights);
}
catch (Exception)
{
print("[" + transform.root.gameObject.name + "] Save error");
}
}
void SaveWeights(string path, NeuralWeights neuralWeights)
{
using (FileStream fs = new FileStream(path, FileMode.Create))
{
XmlSerializer xSer = new XmlSerializer(typeof(NeuralWeights));
xSer.Serialize(fs, neuralWeights);
}
}
// Use this for initialization
void Start()
{
childFolder = new GameObject();
childFolder.name = "[" + transform.root.gameObject.name + "] Childs";
stats = new NeuralChildObject();
InvokeRepeating("mutationUpdate", 1, 1);
startPosition = transform.position;
startRotation = transform.rotation;
stats.LastPosition = startPosition;
ignoreCollide = ignoreFirstCollide;
Debug.Log("[" + transform.root.gameObject.name + "] Generation " + generation);
results = new double[4];
points = new double[population];
sensors = new double[10];
networks = new Network[population];
newNetworks = new NeuralNetwork.NetworkModels.Network(parameters[0], new int[] { 8, 8, 8 }, 4, 2, 1);
gameObjectsChilds = new GameObject[population];
gameObjectsChilds[0] = this.gameObject;
NeuralWeights loadedWeightsValues = null;
if (LoadLastNerual)
{
string m_Path = Application.dataPath + "/" + transform.root.gameObject.name + ".xml";
print(m_Path);
loadedWeightsValues = Load(m_Path);
if (loadedWeightsValues != null)
{
bestScore = loadedWeightsValues.bestScore;
generation = loadedWeightsValues.Generation;
print("[" + transform.root.gameObject.name + "] LoadedWeights");
}
}
if (newNetworkVersion)
{
if (loadedWeightsValues != null)
{
newNetworks.HiddenLayers = loadedWeightsValues.HiddenLayers;
newNetworks.InputLayer = loadedWeightsValues.InputLayer;
newNetworks.OutputLayer = loadedWeightsValues.OutputLayer;
}
for (int i = 1; i < population; i++)
{
//Spawn childs if wanted and can
if (spawnChild && child != null)
{
SpawnChild();
}
}
}
else
{
networks[0] = new Network(parameters);
for (int i = 1; i < population; i++)
{
//Spawn childs if wanted and can
if (spawnChild && child != null)
{
SpawnChild();
}
if (loadedWeightsValues == null)
{
networks[i] = new Network(parameters);
}
else
{
networks[i] = new Network(parameters);
networks[i].setWeights(loadedWeightsValues.weights);
networks[i] = new Network(this, networks[i]);
}
}
}
}
