private void GetFitness(NeuralNetwork bot, bool visible = false)
{
bot.fitness = 0;
for (int i = 0; i < TEST_CASES; i++)
{
/* modify depending on what you want to predict, this is all that changes from problem to problem
* ------------------------------------------------------------------------------------------------*/
SnakeGame game = new SnakeGame(10);
int size = game.boardSize;
while (game.gameInProgress)
{
double[] inputs = new double[16];
int[][] directions = new int[8][];
int idx = 0;
for (int x = -1; x < 2; x++)
{
for (int y = -1; y < 2; y++)
{
if (x != 0 || y != 0)
{
directions[idx++] = new int[] { x, y }
}
;
}
}
for (int j = 0; j < 8; j++)
{
int[] position = new int[2] {
game.snake.headLocation.X, game.snake.headLocation.Y
};
double distance = 1;
inputs[2 * j + 1] = 0;
bool foundSnake = false;
while (true)
{
position[0] += directions[j][0];
position[1] += directions[j][1];
if (position[0] == -1 || position[0] == size || position[1] == -1 || position[1] == size)
{
if (!foundSnake)
{
inputs[2 * j] = 1.0 / (distance * distance);
}
break;
}
BoardElements current = game.board[position[0], position[1]];
switch (current)
{
//case BoardElements.Mine:
case BoardElements.Snake:
if (!foundSnake)
{
inputs[2 * j] = 1.0 / (distance * distance);
foundSnake = true;
}
break;
case BoardElements.Apple:
inputs[2 * j + 1] = 1.0;
break;
}
distance++;
if (foundSnake)
{
break;
}
}
}
bot.SetInputs(inputs);
double[] outputs = bot.Predict();
int index = 0;
double max = outputs[0];
for (int k = 0; k < 4; k++)
{
if (outputs[k] > max)
{
index = k;
max = outputs[k];
}
}
switch (index)
{
case 0:
game.changeDirection(-1, 0);
break;
case 1:
game.changeDirection(1, 0);
break;
case 2:
game.changeDirection(0, -1);
break;
case 3:
game.changeDirection(0, 1);
break;
default:
break;
}
if (visible)
{
Console.CursorVisible = false;
game.advance(true);
Thread.Sleep(200);
}
else
{
game.advance();
}
}
bot.fitness += (int)game.points;
}
/* stay inside this for loop
* ------------------------------------------------------------------------------------------------*/
}
}
static void PlaySnake()
{
GeneticAlg_Snake simulation = new GeneticAlg_Snake(250, 16, 10, 4);
for (int _ = 0; _ < 500; _++)
{
simulation.AdvanceGeneration();
}
NeuralNetwork bot = simulation.bestBot;
Console.WriteLine("Play?");
Console.WriteLine("(Y)Yes");
Console.WriteLine("(N)No");
string input = Console.ReadLine();
while (input.ToUpper() == "Y")
{
SnakeGame game = new SnakeGame(10);
int size = game.boardSize;
while (game.gameInProgress)
{
double[] inputs = new double[16];
int[][] directions = new int[8][];
int idx = 0;
for (int x = -1; x < 2; x++)
{
for (int y = -1; y < 2; y++)
{
if (x != 0 || y != 0)
{
directions[idx++] = new int[] { x, y }
}
;
}
}
for (int j = 0; j < 8; j++)
{
int[] position = new int[2] {
game.snake.headLocation.X, game.snake.headLocation.Y
};
double distance = 1;
inputs[2 * j + 1] = 0;
bool foundSnake = false;
while (true)
{
position[0] += directions[j][0];
position[1] += directions[j][1];
if (position[0] == -1 || position[0] == size || position[1] == -1 || position[1] == size)
{
if (!foundSnake)
{
inputs[2 * j] = 1.0 / (distance * distance);
}
break;
}
BoardElements current = game.board[position[0], position[1]];
switch (current)
{
case BoardElements.Snake:
if (!foundSnake)
{
inputs[2 * j] = 1.0 / (distance * distance);
foundSnake = true;
}
break;
case BoardElements.Apple:
inputs[2 * j + 1] = 1.0;
break;
}
distance++;
if (foundSnake)
{
break;
}
}
}
bot.SetInputs(inputs);
double[] outputs = bot.Predict();
int index = 0;
double max = outputs[0];
for (int k = 0; k < 4; k++)
{
if (outputs[k] > max)
{
index = k;
max = outputs[k];
}
}
switch (index)
{
case 0:
game.changeDirection(-1, 0);
break;
case 1:
game.changeDirection(1, 0);
break;
case 2:
game.changeDirection(0, -1);
break;
case 3:
game.changeDirection(0, 1);
break;
default:
break;
}
Console.Clear();
game.advance(true);
Thread.Sleep(500);
}
Console.WriteLine("Play?");
Console.WriteLine("(Y)Yes");
Console.WriteLine("(N)No");
input = Console.ReadLine();
}
}