public void Train()
{
for (int i =0; i < iterations;i++)
{
while (snake.GameOver==false)
{
SnakeGame temp = (SnakeGame)snake.Clone();
}
}
}
public void Train()
{
int t = 0;
SnakeGame temp = new SnakeGame((SnakeGame)snake.Clone());
while (t < iterations)
{
Console.WriteLine("Iteration:" + t);
List <NeuralNetwork> newPop = new List <NeuralNetwork>();
while (newPop.Count < population.Count)
{
if (temp.gameOver == true)
{
temp = new SnakeGame((SnakeGame)snake.Clone());
}
NeuralNetwork bestNN1 = new NeuralNetwork();
NeuralNetwork bestNN2 = new NeuralNetwork();
int bestResult1 = -1;
int bestResult2 = -1;
for (int i = 0; i < 10; i++)
{
int nextnum = Rgen.Next(population.Count);
NeuralNetwork curNN = population[i];
//int curResult = playGameGetScore(curNN);
int curResult = getResult(curNN, new SnakeGame((SnakeGame)temp.Clone()));
if (curResult > bestResult1)
{
bestResult1 = curResult;
bestNN1 = curNN;
}
}
for (int i = 0; i < 10; i++)
{
int nextnum = Rgen.Next(population.Count);
NeuralNetwork curNN = population[i];
//int curResult = playGameGetScore(curNN);
int curResult = getResult(curNN, new SnakeGame((SnakeGame)temp.Clone()));
if (curResult > bestResult2)
{
bestResult2 = curResult;
bestNN2 = curNN;
}
}
NeuralNetwork crossedNN = crossGen(bestNN1, bestNN2);
crossedNN = Mutate(crossedNN);
newPop.Add(crossedNN);
}
// int nextnum2 = Rgen.Next(newPop.Count);
//temp.MakeMove(newPop[nextnum2].calculateDirection(temp.outputBox()));
List <NeuralNetwork> newList = new List <NeuralNetwork>(newPop.Count);
foreach (NeuralNetwork item in newPop)
{
newList.Add(item);
}
population = newList;
temp.moveHead(population[0].calculateDirection(temp.getInputs()));
t++;
}
}
