public void advance(char dir, apple apl, snake[] snakes, bool printapl)
{
if (l > 2)
{
if (Save == 'w' && dir == 's')
{
dir = Save;
}
if (Save == 's' && dir == 'w')
{
dir = Save;
}
if (Save == 'a' && dir == 'd')
{
dir = Save;
}
if (Save == 'd' && dir == 'a')
{
dir = Save;
}
}
ttl--;
num++;
if (!alive)
{
if (l > 0)
{
l--;
}
else
{
delete();
Xsnake[0] = -1;
Ysnake[0] = -1;
delete();
}
}
else
{
runTime++;
for (int i = l; i > 0; i--)
{
Xsnake[i] = Xsnake[i - 1];
Ysnake[i] = Ysnake[i - 1];
}
if (dir == 's')
{
Ysnake[0]++;
}
if (dir == 'w')
{
Ysnake[0]--;
}
if (dir == 'd')
{
Xsnake[0]++;
}
if (dir == 'a')
{
Xsnake[0]--;
}
if ((apl.appleX() == Xsnake[0]) && (apl.appleY() == Ysnake[0]))
{
l++;
num = 0;
apl.newCord(snakes, s);
if (printapl)
{
apl.print();
}
//ttl = ((ttl + ttlConst) * 6) / 10;
ttl = ttl + ttlConst;
}
}
Save = dir;
}
// the evolution function for the machine learning.
// gets the number of snakes that plays simultaneously (Competing with each other).
static snake Evolution(int snknum)
{
snake[] snakes = new snake[snknum];
for (int i = 0; i < snakes.Length; i++)
{
snakes[i] = new snake(i, s);
}
for (int i = 0; i < snakes.Length; i++)
{
snakes[i].newCord(snakes, s);
}
bool erase = false;
char dir = ' '; //snake diraction by the neural network results.
bool life = true;
bool othersLife = true;
snakes1 = new snake[60]; // the number of snakes in every generation
int numOfGeneration = 100000000;
int evr = 1; // the num of iterations each snake do in one generation
int a = 40; // snakes1.length - a = the num of new random snakes.
int b = 5; // the num of parents snakes
int c = 10; // the num of snakes that survives to the next generation (includes b)
// a - (b + c) = the number of childrens.
char pressedKey = ' '; // changes to the key pressed by the user
for (int i = 0; i < snakes1.Length; i++)
{
snakes1[i] = new snake(0, s);
snakes1[i].AIPrep(snakes);
}
Console.WriteLine("if you already have a saved version and want to keep training it, please write the version num. Otherwise write anything else.");
int ErlySnk = int.Parse(Console.ReadLine());
Console.Beep(261, 50);
Console.Clear();
PrintBoard();
//loading the save version to all the snakes. Also adding mutations.
snakes1[0].Load(ErlySnk);
snakes1[0].snksScore = 10000;
for (int i = 1; i < snakes1.Length; i++)
{
snakes1[i].Load(ErlySnk);
snakes1[i].Change(10);
}
for (int t = 0; t < numOfGeneration; t++)
{
Console.SetCursorPosition(0, s);
Console.WriteLine("Press '*' to stop the learning and save the neural network to file.");
Console.WriteLine("Press 'w' to watch the current snake.");
Console.WriteLine((t / (numOfGeneration + 0.0)) * 100 + "% (epoch " + t + " ) ");
for (int x = 0; x < snakes1.Length; x++)
{
if ((x / (snakes1.Length + 0.0)) * 100 % 10 == 0)
{
Console.SetCursorPosition(0, s + 3);
Console.WriteLine((x / (snakes1.Length + 0.0)) * 100 + "% ");
}
//initialization of variables before the game begins
for (int i = 0; i < snakes.Length; i++)
{
snakes[i] = new snake(i, s);
snakes[i].newCord(snakes, s);
snakes[i].l = 1;
}
life = true;
apple apl = new apple(snakes, s);
snakes[0] = snakes1[x];
snakes[0].newCord(snakes, s);
double score = 0;
for (int m = 0; m < evr; m++)
{
apl.newCord(snakes, s);
// print the current game state to the screan
if ((Console.KeyAvailable || pressedKey == 'w') && x > snakes1.Length - a)
{
if (Console.KeyAvailable)
{
pressedKey = Console.ReadKey().KeyChar;
}
Console.Clear();
PrintBoard();
Console.Write(x + " / " + snakes1.Length);
apl.print();
}
while (Console.KeyAvailable)
{
pressedKey = Console.ReadKey().KeyChar;
}
snakes[0].l = 1; //initial snake length
//one game
while (life)
{
if (erase && (pressedKey != 'w'))
{
Console.Clear();
PrintBoard();
erase = false;
}
for (int i = 0; i < snakes.Length; i++)
{
if (i == 0)
{
// one move of the tested snake, according to the neural network.
dir = snakes[0].AIsnkalg(snakes, apl);
snakes[i].advance(dir, apl, snakes, (Console.KeyAvailable || pressedKey == 'w') && x > snakes1.Length - a);
life = snakes[0].isAlive(snakes);
snakes[0].Save = dir;
}
else
{
//one move of snakes[i], according to the fixed algorithm
dir = snakes[i].snkalg(snakes, apl);
snakes[i].Save = dir;
snakes[i].advance(dir, apl, snakes, (Console.KeyAvailable || pressedKey == 'w') && x > snakes1.Length - a);
othersLife = snakes[i].isAlive(snakes);
if (!othersLife)
{
snakes[i] = new snake(i, s);
snakes[i].newCord(snakes, s);
}
}
// print the current game state to the screan
if ((Console.KeyAvailable || pressedKey == 'w') && x > snakes1.Length - a)
{
erase = true;
if (Console.KeyAvailable)
{
pressedKey = Console.ReadKey().KeyChar;
}
snakes[i].delete();
Console.SetCursorPosition(0, 0);
snakes[i].write(arrows);
Console.SetCursorPosition(2 * s + 1, 0);
Console.ForegroundColor = ConsoleColor.White;
Console.WriteLine("score: " + snakes1[x].score());
if (i == 0)
{
Thread.Sleep(50);
}
apl.print();
}
}
}
snakes[0].ttl = snakes[0].ttlConst;
life = true;
snakes[0].alive = true;
snakes[0].runTime = 0;
snakes[0].l = 1;
snakes[0].bonus = 0;
snakes[0].newCord(snakes, s);
score += snakes[0].snksScore;
snakes[0].snksScore = 0;
}
score = score / (evr * 1.0);
double temp = -0.5;
if (snakes1[x].Right)
{
temp += 0.5;
}
if (snakes1[x].Left)
{
temp += 0.5;
}
if (snakes1[x].Straight)
{
temp += 0.5;
}
score *= temp;
snakes1[x].Right = false;
snakes1[x].Left = false;
snakes1[x].Straight = false;
snakes1[x] = snakes[0];
snakes1[x].snksScore = score;
}
Console.WriteLine("last epoch's first place score in this epoch: " + snakes1[snakes1.Length - 1].snksScore + " ");
Sort(0, snakes1.Length - 1); // sort snakes1 by score
if (pressedKey == '*')
{
return(snakes1[snakes1.Length - 1]); // returning the snake with the best score
}
Console.SetCursorPosition(0, s + 5);
Console.ForegroundColor = ConsoleColor.White;
for (int i = 0; i < 10; i++)
{
Console.WriteLine((i + 1) + ": " + snakes1[snakes1.Length - i - 1].snksScore + " ");
}
Console.SetCursorPosition(0, s + 3);
for (int x = 0; x < snakes1.Length; x++)
{
if (x < snakes1.Length - a)// create new random snakes
{
snakes1[x] = new snake(0, s);
snakes1[x].AIPrep(snakes);
}
else if (x < (snakes1.Length) - c) // create snakes childs
{
snakes1[x] = new snake(0, s);
snakes1[x].AIPrep(snakes);
snakes1[x].Load(snakes1[snakes1.Length - x % b - 1].nn); // duplicating a snake into this snake
snakes1[x].Change(rnd.NextDouble() * 8 + 4); // add mutations
}
snakes1[x].l = 1;
snakes1[x].alive = true;
snakes1[x].runTime = 0;
snakes1[0].newCord(snakes, s);
snakes1[x].snksScore = 0;
}
}
return(snakes1[snakes1.Length - 1]); // returning the snake with the best score
}