void Restart()
{
isRestart = true;
timer1.Enabled = false;
timerdanbay.Enabled = false;
timerbongbay.Enabled = false;
superfood = new SuperFood();
s = 2;
tatspace = true;
dan1 = new Dan1();
dan2 = new Dan2();
dan3 = new Dan3();
sodan = 2; dem = 0;
diemn = score; //if (diemcao < diemn) { diemcao = diemn;CustomMsgBox.Show("Có muốn lưu danh sử sách hay không? :)))","Bạn Đạt Điểm Cao", "Ok", "Để lần sau"); toolStripStatusLabelpro.Text = caothu; }
//MessageBox.Show("Thua rồi :)) choi lai de");
start.Text = "Bấm phím cách để bắt đầu trò chơi";
score = 0;
chanbay = new ChanBay();
bongbay = new BongBay();
bong = new Bong();
van = new Van();
diem.Text = "Điểm:";
network.breedNetworks(gameIndex);
while (true)
{
if (DataGame.IsAllGameFailed())
{
Thread.Sleep(500);
DataGame.ResetGameState();
for (int i = 0; i < 5; i++)
{
if (gameIndex == i)
{
Thread.Sleep(i * 200);
}
}
watch = Stopwatch.StartNew();
timer1.Enabled = true;
left = false; right = false;
start.Text = "";
tatspace = false;
//SendKey("B");
break;
}
Thread.Sleep(50);
}
}
static void Main()
{
Application.EnableVisualStyles();
Application.SetCompatibleTextRenderingDefault(false);
int populationSize = 10;
DataGame.InnitGameState(populationSize);
DataGame[] lstDataGame = new DataGame[populationSize];
ANN NeuralNetwork = new ANN(ref lstDataGame, populationSize);
NeuralNetwork.createFirstGeneration();
for (int i = 0; i < lstDataGame.Length - 1; i++)
{
Task.Run(() =>
{
App(ref NeuralNetwork, i);
});
Thread.Sleep(1000);
}
Application.Run(new Form1(ref NeuralNetwork, lstDataGame.Length - 1));
}
public void breedNetworks(int gameIndex)
{
// updates the score
weightsList[gameIndex].fitness = lstgame[gameIndex].GameTime + lstgame[gameIndex].Score;
averageFitness += weightsList[gameIndex].fitness;
maxFitness = maxFitness > weightsList[gameIndex].fitness ? maxFitness : weightsList[gameIndex].fitness;
if (DataGame.IsAllGameFailed())
{
generation++;
Debug.WriteLine("GEN: " + generation + " | AVG: " + averageFitness / (float)POPULATION_SIZE + " | MAX: " + maxFitness);
averageFitness = 0;
maxFitness = 0;
weightsList = weightsList.OrderByDescending(wi => wi.fitness).ToList();
// starting with a large mutation rate so there's will be more solutions to choose from
if (weightsList[0].fitness < 10)
{
MUTATION_RATE = 0.9;
}
else if (weightsList[0].fitness < 50 && weightsList[0].fitness >= 10)
{
MUTATION_RATE = 0.2;
}
else
{
MUTATION_RATE = 0.05;
}
// adding better solutions from the other instances (if any)
if (nextWeightsList.Count + 3 <= POPULATION_SIZE)
{
// the whole synchronization thingy
try
{
if (mmfMutex == null)
{
mmfMutex = Mutex.OpenExisting("mmfMutex");
}
if (mmfMutex.WaitOne())
{
WeightsInfo wi = new WeightsInfo();
wi = dataSharer.getFromMemoryMap();
if (wi == null || wi.fitness < weightsList[0].fitness)
{
if (wi == null)
{
Debug.WriteLine("Updated - NULL -> " + weightsList[0].fitness);
}
if (wi != null)
{
Debug.WriteLine("Updated - " + wi.fitness + " -> " + weightsList[0].fitness);
}
dataSharer.writeToMemoryMap(weightsList[0]);
}
if (wi != null && wi.fitness > weightsList[0].fitness)
{
nextWeightsList.Add(wi);
}
mmfMutex.ReleaseMutex();
}
}
catch (WaitHandleCannotBeOpenedException ex)
{
mmfMutex = new Mutex(true, "mmfMutex");
nextWeightsList.AddRange(weightsList.Take(4));
mmfMutex.ReleaseMutex();
}
// adding elites to the next generation
nextWeightsList.AddRange(weightsList.Take(3));
}
// creating a new generation
while (nextWeightsList.Count < POPULATION_SIZE)
{
WeightsInfo w1 = select();
WeightsInfo w2 = select();
while (w1 == w2)
{
w1 = select();
w2 = select();
}
List <double> gene1 = new List <double>();
List <double> gene2 = new List <double>();
encode(w1, gene1);
encode(w2, gene2);
crossover(gene1, gene2);
if (mutate(gene1))
{
w1 = new WeightsInfo();
}
if (mutate(gene2))
{
w2 = new WeightsInfo();
}
decode(w1, gene1);
decode(w2, gene2);
if (!nextWeightsList.Contains(w1))
{
nextWeightsList.Add(w1);
}
if (!nextWeightsList.Contains(w2))
{
nextWeightsList.Add(w2);
}
}
weightsList.Clear();
nextWeightsList = nextWeightsList.OrderByDescending(wi => wi.fitness).ToList();
weightsList.AddRange(nextWeightsList);
nextWeightsList.Clear();
}
}
