public SimpleNeuralNet getBrain()
{
if (brain == null)
{
brain = new SimpleNeuralNet(network_struct);
}
return(brain);
}
public void inheritBrain(SimpleNeuralNet other, bool mutate)
{
brain = new SimpleNeuralNet(other);
if (mutate)
{
brain.mutate(swap_rate, mutate_rate, swap_strength, mutate_strength);
}
}
void Update()
{
if (brain == null)
{
brain = new SimpleNeuralNet(network_struct);
}
checkConstraint();
fly();
}
public SimpleNeuralNet(SimpleNeuralNet other)
{
all_weights = new List <float[, ]>();
all_results = new List <float[]>();
for (int i = 0; i < other.all_weights.Count; i++)
{
all_weights.Add((float[, ])other.all_weights[i].Clone());
all_results.Add((float[])other.all_results[i].Clone());
}
}
void Update()
{
if (brain == null)
{
brain = new SimpleNeuralNet(network_struct);
}
if (terrain == null)
{
return;
}
if (details == null)
{
updateSetup();
return;
}
energy -= energy_loss;
int dx = (int)((tfm.position.x / terrain_sz.x) * detail_sz.x);
int dy = (int)((tfm.position.z / terrain_sz.y) * detail_sz.y);
// If over grass, eat it, gain energy and spawn offspring
lookAround(dx, dy);
/*if (dx >= 0 && dx < details.GetLength(1) &&
* dy >= 0 && dy < details.GetLength(0) &&
* details[dy, dx] > 0) {
* details[dy, dx] = 0;
* energy += energy_gain;
* if (energy > max_energy)
* energy = max_energy;
* genetic_algo.addOffspring(this);
* }*/
// Die when out of energy
if (energy < 0)
{
energy = 0.0f;
genetic_algo.removeAnimal(this);
}
if (mat != null)
{
mat.color = Color.white * (energy / max_energy);
}
// Update receptor
updateVision();
// Use brain
float[] output = brain.getOutput(vision);
// Act using actuators
float angle = (output[0] * 2.0f - 1.0f) * max_angle;
tfm.Rotate(0.0f, angle, 0.0f);
}
private void HandleKeyPress(object sender, KeyEventArgs e)
{
switch (e.Key)
{
case Key.B:
SimpleNeuralNet.Run(brainWindow);
break;
default:
Game.HandleKeyPress(sender, e);
break;
}
}