public void NeuroShake(double rate)
{
for (int i = 0; i < HiddenLayers.Count; i++)
{
for (int j = 0; j < HiddenLayers[i].Count; j++)
{
for (int w = 0; w < HiddenLayers[i][j].Weights.Length; w++)
{
if (StaticRandom.NextDouble() < rate)
{
HiddenLayers[i][j].Weights[w] = GetRandomWeight();
}
}
}
}
for (int i = 0; i < Outputs.Count; i++)
{
for (int w = 0; w < Outputs[i].Weights.Length; w++)
{
if (StaticRandom.NextDouble() < rate)
{
Outputs[i].Weights[w] = GetRandomWeight();
}
}
}
for (int i = 0; i < Memory.Count; i++)
{
for (int w = 0; w < Memory[i].Weights.Length; w++)
{
if (StaticRandom.NextDouble() < rate)
{
Memory[i].Weights[w] = GetRandomWeight();
}
}
}
/*for (int i = 0; i < 10 * rate; i++)
* {
* if (R.NextDouble() > 0.3)
* {
* var j = R.Next(HiddenLayers.Count);
* var k = R.Next(HiddenLayers[j].Count);
* var prevLayer = j == 0 ? Inputs : HiddenLayers[j - 1];
* var l = R.Next(prevLayer.Count);
* HiddenLayers[j][k].Weights[l] = GetRandomWeight();
* }
* else if (R.NextDouble() > 0.5)
* {
* var j = R.Next(Memory.Count);
* var k = R.Next(HiddenLayers[HiddenLayers.Count - 1].Count);
* Memory[j].Weights[k] = GetRandomWeight();
* }
* else
* {
* var j = R.Next(Outputs.Count);
* var k = R.Next(HiddenLayers[HiddenLayers.Count - 1].Count);
* Outputs[j].Weights[k] = GetRandomWeight();
* }
* }*/
}
public static double GetRandomWeight()
{
return(StaticRandom.NextDouble() * 2 - 1);
}
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++;
}
