public void InitiatePopulation()
{
for (int i = 0; i < populationSize; i++)
{
pop[i] = new GeneticBrain(inputSize, hiddenLayerSize, outputSize, minRandom, maxRandom, this);
}
StartCoroutine("WaitForStart");
}
static void Main()
{
double[] point = new double[2];
//BasicBrain naivebrain = new BasicBrain();
//point = naivebrain.BasicMaximum();
GeneticBrain geneticbrain = new GeneticBrain();
point = geneticbrain.GeneticMaximum();
Console.WriteLine("Found local maximum at (" + Convert.ToString(point[0]) + ", " + Convert.ToString(point[1]) + ").");
Console.WriteLine("Press any key to continue...");
Console.ReadKey();
}
public void NextGeneration()
{
RemovePrevGen();
generationNum++;
List <GeneticBrain> pool = CreatePool();
GeneticBrain[] newPop = new GeneticBrain[populationSize];
for (int i = 0; i < populationSize; i++)
{
newPop[i] = new GeneticBrain(inputSize, hiddenLayerSize, outputSize, minRandom, maxRandom, this);
GeneticBrain parent1 = pool[Random.Range(0, pool.Count)];
GeneticBrain parent2 = pool[Random.Range(0, pool.Count)];
newPop[i].hoWeights = Matrix.MixedMatrix(parent1.hoWeights, parent2.hoWeights, mutationRate, minRandom, maxRandom);
newPop[i].ihWeights = Matrix.MixedMatrix(parent1.ihWeights, parent2.ihWeights, mutationRate, minRandom, maxRandom);
newPop[i].oBias = Matrix.MixedMatrix(parent1.oBias, parent2.oBias, mutationRate, minRandom, maxRandom);
newPop[i].hBias = Matrix.MixedMatrix(parent1.hBias, parent2.hBias, mutationRate, minRandom, maxRandom);
}
pop = newPop;
PopulateScene();
}
public double[] GeneticMaximum()
{
GeneticBrain thisBrain = new GeneticBrain();
const int numWalkers = 500;
double[] final = new double[2];
Random rnd = new Random();
int stepIndex = new int();
// Define a number of walkers on the field to be bred.
GeneticWalker[] walkers = new GeneticWalker[numWalkers];
// Initialize the walkers.
for (int i = 0; i < numWalkers; i++)
walkers[i] = new GeneticWalker();
for (int walkerIndex = 0; walkerIndex < numWalkers; walkerIndex++)
{
for (stepIndex = 0; stepIndex < walkers[walkerIndex].walkerHistory.Length; stepIndex++)
{
int step = rnd.Next(0, 3) - 1;
if (rnd.Next(0, 2) == 1)
{
walkers[walkerIndex].walkerPosition[0] += step * walkers[walkerIndex].dx;
walkers[walkerIndex].walkerHistory[stepIndex] = new Complex(step * walkers[walkerIndex].dx, 0);
}
else
{
walkers[walkerIndex].walkerPosition[1] += step * walkers[walkerIndex].dx;
walkers[walkerIndex].walkerHistory[stepIndex] = new Complex(0, step * walkers[walkerIndex].dx);
}
}
walkers[walkerIndex].height = walkers[walkerIndex].walkerHeight();
}
thisBrain.SortWalkers(ref walkers);
for (int i = 0; i < 1500; i++ )
{
GeneticWalker[] temp = walkers;
thisBrain.SortWalkers(ref temp);
thisBrain.BreedWalkers(ref walkers);
thisBrain.WalkFromHistory(ref walkers);
thisBrain.SortWalkers(ref walkers);
if (temp[0].height > walkers[0].height)
walkers = temp;
Console.WriteLine(Convert.ToString(i)+": "+Convert.ToString(Math.Sqrt(Math.Pow(walkers[0].walkerPosition[0]-3.4,2)+Math.Pow(walkers[0].walkerPosition[1]+4,2))));
}
thisBrain.SortWalkers(ref walkers);
final = walkers[0].walkerPosition;
return final;
}
