private void StartNewGeneration()
{
//Turn off Models
float[] lastFitness = new float[Population.Length];
string[] lastParents = new string[Population.Length];
float[] lastMutation = new float[Population.Length];
foreach (var individual in Population)
{
individual.active = false;
}
//fit parens, mut
//Sort fitness.
Model[] Sorted = Population.OrderBy(p => p.fitnes).ToArray();
//Remember last 3 best
lastbest = Sorted[Sorted.Length - 1].id;
for (int i = 0; i < lastThreeBest.Length; i++)
{
lastThreeBest[i] = newThreeBest[i];
newThreeBest[i] = Sorted[Sorted.Length - 1 - i].fitnes;
}
string ratting;
ratting = "Last Winners\n";
for (int i = 0; i < lastThreeBest.Length; i++)
{
ratting += (i + 1) + " F:" + newThreeBest[i].ToString("f2") + " LastF:" + lastThreeBest[i].ToString("f2") + " Prog:" + (newThreeBest[i] - lastThreeBest[i]).ToString("f2") + "\n";
}
UserInterface.Ratting.text = ratting;
//Save Best Half and Create new Half from best, aka Algorithm evolutionStrategy
int k = Sorted.Length - 1;
for (int i = 0; i < Sorted.Length; i++)
{
string parents = "NoN";
lastFitness[Sorted[i].id] = Sorted[i].fitnes;
Sorted[i].lastMutation = 0;
int half = (Sorted.Length / 2);
if (i < half)
{
//create a child
int whereCut = UnityEngine.Random.Range(2, SchematSize - 3);
//build new Neural network
float[] Weights = new float[SchematSize];
Sorted[k].neuralNetwork.WrtieWeights(0, whereCut, ref Weights);
Sorted[k - 1].neuralNetwork.WrtieWeights(whereCut, SchematSize - 1, ref Weights);
parents = Sorted[k].id + "x" + Sorted[k - 1].id;
Sorted[i].ColorMixer(Sorted[k].MySkin.material.color, Sorted[k - 1].MySkin.material.color);
k--;
//implement new neural network
Sorted[i].neuralNetwork.ApplyNewWeights(Weights);
//Mutation
Sorted[i].Mutate(Mutation);
}
else
{
}
lastParents[Sorted[i].id] = parents;
lastMutation[Sorted[i].id] = Sorted[i].lastMutation;
float lotto = UnityEngine.Random.Range(0f, 100f);
Sorted[i].ResetPostion();
}
Generation++;
UserInterface.GenerationInformation.text = Generation + "\t:Generation";
//Turn On Models
foreach (var individual in Population)
{
individual.active = true;
}
dataRecorder.NexGenRecord(LifeTime, Mutation, lastFitness, lastParents, lastMutation);
UserInterface.DataText.text = dataRecorder.ShowData();
}