private void InitSnakes()
{
for (int i = 0; i < populationCount; i++)
{
fields.Add(new Field(fieldSize, fieldSize, i * (int)DateTime.Now.Ticks));
var neuroNetwork = new NeuroNetwork(snakeInputs, hiddenLayersConfig[StaticRandom.Next(hiddenLayersConfig.Count)], snakeOutputs, snakeMemory);
population.Add(new Snake(fields[i], neuroNetwork));
}
}
private void Initialize()
{
var point = new Point(StaticRandom.Next(1, Field.Width - 1), StaticRandom.Next(1, Field.Height - 1));
while (Field[point] != Content.EMPTY)
{
point = new Point(StaticRandom.Next(1, Field.Width - 1), StaticRandom.Next(1, Field.Height - 1));
}
Field[point] = Content.SNAKE;
body.Add(point);
}
public void PlaceFood()
{
var point = new Point(StaticRandom.Next(Width), StaticRandom.Next(Height));
int count = 0;
while (this[point] != Content.EMPTY)
{
if (++count > 1000)
{
throw new Exception();
}
point = new Point(StaticRandom.Next(Width), StaticRandom.Next(Height));
}
this[point] = Content.FOOD;
Food.Add(point);
}
public NeuroNetwork(int inputs, List <int> hiddenLayers, int outputs, int memory = 0, bool generate = true)
{
Inputs = new List <Neuron>();
HiddenLayers = new List <List <Neuron> >();
for (int i = 0; i < hiddenLayers.Count; i++)
{
HiddenLayers.Add(new List <Neuron>());
}
Outputs = new List <Neuron>();
Memory = new List <Neuron>();
if (generate)
{
GenerateRand(inputs, hiddenLayers, outputs, memory);
}
Color = Color.FromArgb(StaticRandom.Next(256), StaticRandom.Next(256), StaticRandom.Next(256));
}
public Snake(Field field, NeuroNetwork neuroNetwork)
{
Field = field;
field.Snake = this;
NeuroNetwork = neuroNetwork;
neuroNetwork.Snake = this;
body = new List <Point>();
Energy = 50;
Rotation = StaticRandom.Next(4);
lastTurns = new List <double> {
0, 0, 0
};
Initialize();
}
private void CreatePopulation()
{
dead.Sort(new SnakeComparer());
dead.Reverse();
if (topSnake == null || dead[0].Fitness > topSnake.Fitness)
{
topSnake2 = topSnake;
topSnake = dead[0];
}
if (topSnake2 == null)
{
topSnake2 = dead[1];
}
scores["maxFitness"] = Math.Max(scores["maxFitness"], dead[0].Fitness);
scores["lastFitness"] = dead[0].Fitness;
if (dead[0].Fitness == 0)
{
throw new Exception();
}
var fieldCount = 0;
/*for (int i = 0; i < populationCount * 0.0; i++)
* {
* var neuroNetwork = dead[0].NeuroNetwork.Copy();
* neuroNetwork.NeuroShake(shakeRate);
* population.Add(new Snake(fields[fieldCount], neuroNetwork));
* fieldCount++;
* }*/
for (int i = 0; i < populationCount * 0.3; i++)
{
var neuroNetwork = topSnake.NeuroNetwork.Copy();
neuroNetwork.Cross(dead[0].NeuroNetwork);
neuroNetwork.NeuroShake(shakeRate);
population.Add(new Snake(fields[fieldCount], neuroNetwork));
fieldCount++;
}
for (int i = 0; i < populationCount * 0.3; i++)
{
var neuroNetwork = topSnake.NeuroNetwork.Copy();
neuroNetwork.NeuroShake(shakeRate);
population.Add(new Snake(fields[fieldCount], neuroNetwork));
fieldCount++;
}
for (int i = 0; i < populationCount * 0.2; i++)
{
var neuroNetwork = topSnake2.NeuroNetwork.Copy();
neuroNetwork.NeuroShake(shakeRate);
population.Add(new Snake(fields[fieldCount], neuroNetwork));
fieldCount++;
}
for (int i = 0; i < populationCount * 0.2; i++)
{
var neuroNetwork = new NeuroNetwork(snakeInputs, hiddenLayersConfig[StaticRandom.Next(hiddenLayersConfig.Count)], snakeOutputs, snakeMemory);
population.Add(new Snake(fields[fieldCount], neuroNetwork));
fieldCount++;
}
foreach (var field in fields)
{
field.ReviewFood();
}
dead.Clear();
populationNumber++;
}
