/// <summary>
/// Initialize Seekers List
/// </summary>
private void InitSeekers()
{
StaticClass.StartSeekerRot = (float)StaticClass.rnd.NextDouble() * MathHelper.TwoPi;
for (int i = 0; i < StaticClass.SeekerNum; i++)
{
NeuralNetwork.NeuralNetwork Neuralnetwork = new NeuralNetwork.NeuralNetwork(
StaticClass.SeekerInputs,
StaticClass.hiddenLayersConfig[StaticClass.rnd.Next(StaticClass.hiddenLayersConfig.Count)],
StaticClass.SeekerOutputs);
SeekerPop.Add(new Seeker(StaticClass.SeekerAnimation, Neuralnetwork, new BotKeys(), StaticClass.StartSeekerPos,
null, Color.White, StaticClass.StartSeekerRot, new Vector2(StaticClass.SeekerAnimation.First().Value.FrameWidth / 2, StaticClass.SeekerAnimation.First().Value.FrameHeight / 2),
new Vector2(StaticClass.CharacterScale), 0, 0));
}
}
public Seeker(Dictionary <string, Animation.Animation> animations, NeuralNetwork.NeuralNetwork Neuralnetwork, BaseKeys keys, Vector2 position,
Rectangle?sourceRectangle, Color color,
float rotation, Vector2 origin, Vector2 scale,
SpriteEffects effects, float layerDepth) :
base(animations.First().Value, position,
sourceRectangle, color,
rotation, origin, scale,
effects, layerDepth)
{
this.animations = animations;
this.keys = keys;
LifeTime = 1;
Score = 0;
this.Neuralnetwork = Neuralnetwork;
Energy = 501;
MainGame.UpdateEvent += update;
}
/// <summary>
/// Create seeker population by the best seekers
/// </summary>
private void CreateSeekerPopulation()
{
// sort dead seekers by the best fitness they achive
DeadSeekers.Sort(new SeekerCompare());
DeadSeekers.Reverse();
// set the best seeker by the most fitness points
if (StaticClass.TopSeeker == null || DeadSeekers[0].Fitness >
StaticClass.TopSeeker.Fitness)
{
StaticClass.TopSeeker2 = StaticClass.TopSeeker;
StaticClass.TopSeeker = DeadSeekers[0];
}
// Change the dictionary
if (StaticClass.TopSeeker2 == null)
{
StaticClass.TopSeeker2 = DeadSeekers[1];
}
StaticClass.Stats["MaxFitness"] = Math.Max(StaticClass.Stats["MaxFitness"],
DeadSeekers[0].Fitness);
StaticClass.Stats["LastFitness"] = DeadSeekers[0].Fitness;
if (DeadSeekers[0].Fitness == 0)
{
throw new Exception();
}
// create green seekers that Their Neural Network Similar the best seeker
for (int i = 0; i < StaticClass.SeekerNum * 0.35; i++)
{
NeuralNetwork.NeuralNetwork Neuralnetwork =
StaticClass.TopSeeker.Neuralnetwork.Copy();
Neuralnetwork.Cross(DeadSeekers[0].Neuralnetwork);
Neuralnetwork.ChangeNeuronWeights(StaticClass.shakeRate);
SeekerPop.Add(new Seeker(StaticClass.SeekerAnimation, Neuralnetwork, new BotKeys(), StaticClass.StartSeekerPos,
null, Color.Green, StaticClass.StartSeekerRot, new Vector2(StaticClass.SeekerAnimation.First().Value.FrameWidth / 2, StaticClass.SeekerAnimation.First().Value.FrameHeight / 2),
new Vector2(StaticClass.CharacterScale), 0, 0));
}
// create blue seekers that Their Neural Network With a little change of the best seeker
for (int i = 0; i < StaticClass.SeekerNum * 0.35; i++)
{
NeuralNetwork.NeuralNetwork Neuralnetwork =
StaticClass.TopSeeker.Neuralnetwork.Copy();
Neuralnetwork.ChangeNeuronWeights(StaticClass.shakeRate);
SeekerPop.Add(new Seeker(StaticClass.SeekerAnimation, Neuralnetwork, new BotKeys(), StaticClass.StartSeekerPos,
null, Color.Blue, StaticClass.StartSeekerRot,
new Vector2(StaticClass.SeekerAnimation.First().Value.FrameWidth / 2, StaticClass.SeekerAnimation.First().Value.FrameHeight / 2),
new Vector2(StaticClass.CharacterScale), 0, 0));
}
// create red seekers that Their Neural Network With a little change of the second best seeker
for (int i = 0; i < StaticClass.SeekerNum * 0.2; i++)
{
NeuralNetwork.NeuralNetwork Neuralnetwork =
StaticClass.TopSeeker2.Neuralnetwork.Copy();
Neuralnetwork.ChangeNeuronWeights(StaticClass.shakeRate);
SeekerPop.Add(new Seeker(StaticClass.SeekerAnimation, Neuralnetwork, new BotKeys(), StaticClass.StartSeekerPos,
null, Color.Red, StaticClass.StartSeekerRot,
new Vector2(StaticClass.SeekerAnimation.First().Value.FrameWidth / 2, StaticClass.SeekerAnimation.First().Value.FrameHeight / 2),
new Vector2(StaticClass.CharacterScale), 0, 0));
}
// create regular seekers that Their Neural Network is Random
for (int i = 0; i < StaticClass.SeekerNum * 0.1; i++)
{
NeuralNetwork.NeuralNetwork Neuralnetwork = new NeuralNetwork.NeuralNetwork(
StaticClass.SeekerInputs, StaticClass.hiddenLayersConfig[
StaticClass.rnd.Next(StaticClass.hiddenLayersConfig.Count)],
StaticClass.SeekerOutputs);
SeekerPop.Add(new Seeker(StaticClass.SeekerAnimation, Neuralnetwork, new BotKeys(), StaticClass.StartSeekerPos,
null, Color.White, StaticClass.StartSeekerRot,
new Vector2(StaticClass.SeekerAnimation.First().Value.FrameWidth / 2, StaticClass.SeekerAnimation.First().Value.FrameHeight / 2),
new Vector2(StaticClass.CharacterScale), 0, 0));
}
StaticClass.LiveTopSeeker = null;
DeadSeekers.Clear();
StaticClass.PopulationNumber++;
StaticClass.Stats["NumOfFounds"] = StaticClass.NumOfFounds;
StaticClass.NumOfFounds = 0;
}