public void ResetThem2()
{
for (int i = 0; i < size; i++)
{
snakes2[i] = new Snake2(snakes2[i]);
}
}
private void PlaySecondPopulation()
{
firstBrain = false;
it = 0;
actualEpoch = 0;
InitializeSecondPopulation();
actualSnake2 = p.snakes2[it];
p.BestOverall2 = p.snakes2[0];
}
public Snake2(Snake2 origin)
{
headPosition = new Position(r.Next(5, mapSize - 5), r.Next(5, mapSize - 5));
velocity = new Position(1, 0);
tailPosition = new List <Position>();
tailPosition.Add(new Position(headPosition.X - 1, headPosition.Y));
tailPosition.Add(new Position(headPosition.X - 2, headPosition.Y));
tailPosition.Add(new Position(headPosition.X - 3, headPosition.Y));
tailPosition.Add(new Position(headPosition.X - 4, headPosition.Y));
brain = CopyBrain(origin.brain);
brain2 = CopyBrain(origin.brain2);
usedSecondBrain = false;
fitness2 = 0;
timeOfLife = 0;
fitness = origin.fitness;
eatenFood = 0;
alive = true;
timetoDie = 4 * mapSize;
livesLeft = howManyLives;
SpawnFood();
previousHeadPosition = new Position(-1, -1);
}
public Snake2[] Crossover(Snake2 s)
{
Snake2[] tab = new Snake2[2];
Snake2 baby1 = new Snake2();
Snake2 baby2 = new Snake2();
int warstwa = r.Next(0, brain2.Layers.Count() - 2);
int neuron = r.Next(0, brain2.Layers[warstwa].Neurons.Count() - 1);
bool przed = true;
for (int i = 0; i < brain2.Layers.Count() - 1; i++)
{
for (int j = 0; j < brain2.Layers[i].Neurons.Count(); j++)
{
if (j < neuron && warstwa == i)
{
przed = false;
}
if (przed)
{
for (int k = 0; k < brain2.Layers[i].Neurons[j].Weights.Count(); k++)
{
baby1.brain2.Layers[i].Neurons[j].Weights[k] = brain2.Layers[i].Neurons[j].Weights[k];
baby2.brain2.Layers[i].Neurons[j].Weights[k] = s.brain2.Layers[i].Neurons[j].Weights[k];
}
}
else
{
for (int k = 0; k < brain2.Layers[i].Neurons[j].Weights.Count(); k++)
{
baby2.brain2.Layers[i].Neurons[j].Weights[k] = brain2.Layers[i].Neurons[j].Weights[k];
baby1.brain2.Layers[i].Neurons[j].Weights[k] = s.brain2.Layers[i].Neurons[j].Weights[k];
}
}
}
}
tab[0] = baby1;
tab[1] = baby2;
return(tab);
}
public void Crossover2()
{
int howManyBest = 5;
List <Snake2> best = ChooseBest2(howManyBest);
best.Add(new Snake2(BestOverall2));
List <Snake2> childs = new List <Snake2>();
Snake2[] dzieci = new Snake2[2];
for (int k = 0; k < (size - 20) / 60; k++) //180
{
for (int i = 0; i < howManyBest + 1; i++)
{
for (int j = 0; j < howManyBest + 1; j++)
{
if (i != j)
{
dzieci = best[i].Crossover(best[j]);
childs.AddRange(dzieci);
}
}
}
}
for (int i = 0; i < 2; i++) //10
{
childs.AddRange(best);
}
for (int i = 0; i < 10; i++) //10
{
childs.Add(new Snake2());
}
for (int i = 0; i < snakes2.Count; i++)
{
snakes2[i].brain2 = childs[i].CopyBrain(childs[i].brain2);
}
}
private void dispatcherTimer_Tick(object sender, EventArgs e)
{
if (firstBrain)
{
if (actualSnake.alive)
{
Play();
}
else
{
actualSnake.CalculateFitness();
ActBlock.Text = actualSnake.fitness.ToString();
if (it < p.size)
{
actualSnake = p.snakes[it++];
}
else
{
if (actualEpoch < maxEpochs)
{
double max = p.BestSnake.fitness;
double maxFood = p.BestSnake.eatenFood;
EpochBlock.Text = (actualEpoch + 1).ToString();
MeanBlock.Text = Math.Truncate(p.FitnessAVG).ToString();
MaxBlock.Text = max.ToString();
wyniki.Add(String.Format(actualEpoch + ". AVG:" + Math.Truncate(p.FitnessAVG) + " MAX: " + max + " Zjedzone: " + maxFood));
if (p.BestSnake.fitness > p.BestOverall.fitness)
{
p.BestOverall = new Snake(p.BestSnake);
}
p.UseGeneticOperations();
it = 0;
actualSnake = p.snakes[it];
actualEpoch++;
}
else
{
//SaveResult();
Draw = true;
dispatcherTimer.Interval = new TimeSpan(0, 0, 0, 0, 30);
PlayBest();
//MessageBox.Show(String.Format("Zjedzone: " + p.BestOverall.eatenFood));
//SaveWinner();
//firstBrain = false;
//it = 0;
//actualEpoch = 0;
//InitializeSecondPopulation();
//actualSnake2 = p.snakes2[it];
//p.BestOverall2 = p.snakes2[0];
}
}
}
}
else //Kiedy mamy wyuczony pierwszy mózg...
{
if (actualSnake2.alive)
{
Play2();
}
else
{
actualSnake2.CalculateFitness();
ActBlock.Text = actualSnake2.fitness.ToString();
if (it < p.size)
{
actualSnake2 = p.snakes2[it++];
}
else
{
if (actualEpoch < maxEpochs)
{
double max = p.BestSnake2.fitness;
double maxFood = p.BestSnake2.eatenFood / Snake.howManyLives;
EpochBlock.Text = (actualEpoch + 1).ToString();
MeanBlock.Text = Math.Truncate(p.FitnessAVG2).ToString();
MaxBlock.Text = max.ToString();
wyniki.Add(String.Format(actualEpoch + ". AVG:" + Math.Truncate(p.FitnessAVG2) + " MAX: " + max + " Zjedzone: " + maxFood));
if (p.BestSnake2.fitness > p.BestOverall2.fitness)
{
p.BestOverall2 = new Snake2(p.BestSnake2);
}
p.UseGeneticOperations2();
it = 0;
actualSnake2 = p.snakes2[it];
actualEpoch++;
}
else
{
//SaveResult();
Draw = true;
dispatcherTimer.Interval = new TimeSpan(0, 0, 0, 0, 30);
PlayBest2();
MessageBox.Show(String.Format("Zjedzone: " + p.BestOverall2.eatenFood));
//SaveWinner();
}
}
}
}
}
private void PlayBest2()
{
actualSnake2 = new Snake2(p.BestOverall2);
}
private void LoadWinner2(string plik)
{
actualEpoch = maxEpochs;
it = p.size;
string s = File.ReadAllText(plik);
List <string> s2 = s.Split(new string[] { "\r\n" }, StringSplitOptions.None).ToList();
string[] s3;
double[] d;
ActivationNetwork brain = new ActivationNetwork(new BipolarSigmoidFunction(), 12, 8, 4);
int row = 0;
for (int i = 0; i < brain.Layers.Length; i++)
{
for (int j = 0; j < brain.Layers[i].Neurons.Length; j++)
{
s3 = s2[row].Split(';'); //bierzemy wiersz
d = new double[s3.Length];
for (int k = 0; k < s3.Length; k++) //robimy z niego double
{
d[k] = Convert.ToDouble(s3[k]);
}
//Wpisujemy dane do neuronu
for (int k = 1; k < d.Length; k++)
{
brain.Layers[i].Neurons[j].Weights[k - 1] = d[k];
}
(brain.Layers[i].Neurons[j] as ActivationNeuron).Threshold = d[0];
row++;
while (s2[row] == "")
{
row++;
if (row == s2.Count)
{
break;
}
}
}
}
//DRUGI MÓZG
row++;
ActivationNetwork brain2 = new ActivationNetwork(new BipolarSigmoidFunction(), 12, 8, 4);
for (int i = 0; i < brain2.Layers.Length; i++)
{
for (int j = 0; j < brain2.Layers[i].Neurons.Length; j++)
{
s3 = s2[row].Split(';'); //bierzemy wiersz
d = new double[s3.Length];
for (int k = 0; k < s3.Length; k++) //robimy z niego double
{
d[k] = Convert.ToDouble(s3[k]);
}
//Wpisujemy dane do neuronu
for (int k = 1; k < d.Length; k++)
{
brain2.Layers[i].Neurons[j].Weights[k - 1] = d[k];
}
(brain2.Layers[i].Neurons[j] as ActivationNeuron).Threshold = d[0];
row++;
while (s2[row] == "")
{
row++;
if (row == s2.Count)
{
break;
}
}
}
}
actualSnake2 = new Snake2();
actualSnake2.brain = actualSnake2.CopyBrain(brain);
actualSnake2.brain2 = actualSnake2.CopyBrain(brain2);
p.BestOverall2 = new Snake2(actualSnake2);
}
