public OddTest()
{
Console.WriteLine("Welcome to Neural Odd Test Example");
FeedForwardNetwork network = new FeedForwardNetwork(new SigmoidFunction(), 1, 10, 1);
BackPropagationLearning teacher = new BackPropagationLearning(network);
teacher.LearningRate = 0.1;
Random R = new Random(Environment.TickCount);
Console.WriteLine("Training...");
for (int i = 0; i < 1000; i++)
{
Console.Write("[T] Input >> ");
int Input = R.Next(1024);
Console.WriteLine(Input);
teacher.Teach(Binary(Input), (Input % 2 == 0) ? (new double[] { 0 }) : (new double[] { 1 }));
Console.Write("[T] Output >> ");
Console.WriteLine(network.Launch(Binary(Input))[0].ToString());
}
Console.WriteLine("Examing...");
Console.Write("[E] Input >> ");
string userString = Console.ReadLine();
while (userString != "stop")
{
int Number = int.Parse(userString.Split(' ')[0]);
Console.Write("[E] Output >> ");
Print(network.Launch(Binary(Number)));
Console.Write("[E] Input >> ");
userString = Console.ReadLine();
}
Console.WriteLine();
}
public void Teach(double[] Inputs, double[] Outputs)
{
Errors = new double[Network.Layers.Count][];
for (int i = 0; i < Network.Layers.Count; i++)
{
Errors[i] = new double[Network.Layers[i].Neurons.Count];
}
Network.Launch(Inputs);
for (int i = 0; i < Network.Layers[Network.Layers.Count - 1].Neurons.Count; i++)
{
Errors[Network.Layers.Count - 1][i] = (Outputs[i] - Network.Layers[Network.Layers.Count - 1].Neurons[i].OutputImpulse) * (Network.ActivationFunction.Derivative(Network.Layers[Network.Layers.Count - 1].Neurons[i].InputImpulse));
foreach (Link Bridge in Network.Layers[Network.Layers.Count - 1].Neurons[i].Inputs)
{
Errors[Network.Layers.Count - 2][Bridge.FromIndex] += (Bridge.Weight * Errors[Network.Layers.Count - 1][i]);
Bridge.Weight += (LearningRate * Errors[Network.Layers.Count - 1][i] * Bridge.From.OutputImpulse);
}
Network.Layers[Network.Layers.Count - 1].Neurons[i].Bias += (LearningRate * Errors[Network.Layers.Count - 1][i]);
}
for (int i = (Network.Layers.Count - 2); i > 0; i--)
{
for (int j = 0; j < Network.Layers[i].Neurons.Count; j++)
{
Errors[i][j] *= Network.ActivationFunction.Derivative(Network.Layers[i].Neurons[j].InputImpulse);
foreach (Link Bridge in Network.Layers[i].Neurons[j].Inputs)
{
Errors[i - 1][Bridge.FromIndex] += Errors[i][j];
Bridge.Weight += (LearningRate * Errors[i][j] * Bridge.From.OutputImpulse);
}
Network.Layers[i].Neurons[j].Bias += (LearningRate * Errors[i][j]);
}
}
}
public void Think(Vector2 _ghostPosition, Vector2 _pacmanPosition)
{
Vector2 toGhost = Vector2.Zero;
float Alpha = 0f;
if (_ghostPosition != -Vector2.One)
{
toGhost = _ghostPosition - Position;
float AlphaCosine = ((float)Math.Cos(Rotation) * toGhost.X + (float)Math.Sin(Rotation) * toGhost.Y) / toGhost.Length();
float AlphaSine = ((float)Math.Cos(Rotation) * toGhost.Y - (float)Math.Sin(Rotation) * toGhost.X) / toGhost.Length();
Alpha = (AlphaSine < 0) ? (-(float)Math.Acos(AlphaCosine)) : ((float)Math.Acos(AlphaCosine));
}
Vector2 toPacman = Vector2.Zero;
float Beta = 0f;
if (_pacmanPosition != -Vector2.One)
{
toPacman = _pacmanPosition - Position;
float BetaCosine = ((float)Math.Cos(Rotation) * toPacman.X + (float)Math.Sin(Rotation) * toPacman.Y) / toPacman.Length();
float BetaSine = ((float)Math.Cos(Rotation) * toPacman.Y - (float)Math.Sin(Rotation) * toPacman.X) / toPacman.Length();
Beta = (BetaSine < 0) ? (-(float)Math.Acos(BetaCosine)) : ((float)Math.Acos(BetaCosine));
}
double[] Answer = Network.Launch(new double[] { toGhost.Length() / 250, Alpha, toPacman.Length() / 250, Beta });
float Gamma = (float)Answer[0];
//Rotation = MathHelper.Lerp(Rotation, Rotation + (float)Math.Asin(SineGamma), 0.4f);
//Rotation = MathHelper.Lerp(Rotation, Rotation + (float)SineGamma, 0.4f);
Rotation += (float)Gamma;
Rotation %= (float)MathHelper.TwoPi;
}
public void ManualExaming(FeedForwardNetwork _network)
{
Console.Write("[E] Inputs >> ");
string userString = Console.ReadLine();
while (userString != "stop")
{
double[] Inputs = ParseDoubles(userString);
double[] Outputs = _network.Launch(Inputs);
Console.Write("[E] Outputs >> ");
for (int i = 0; i < Outputs.Length; i++)
{
Console.Write(Outputs[i] + " ");
}
Console.WriteLine();
Console.Write("[E] Inputs >> ");
userString = Console.ReadLine();
}
}
