public void Retry()
{
opponent.CloneTo(trainee);
expansion += acceleration;
//move.Reset((float) rng.NextDouble() * expansion);
move.Reset();
Layer layer = move.layers[rng.Next(0, move.layers.Length)];
int n = rng.Next(0, layer._matrix.Length);
int w = rng.Next(0, layer._matrix[0].Length);
float[] weights = new float[layer._matrix[0].Length];
weights.Initialize();
weights[w] = (rng.Next(0, 2) * 2 - 1) * expansion;
layer.SetNeuron(layer._shape.At(n), weights);
Console.WriteLine(trainee.net.layers[0]._matrix[0][0]);
trainee.net.Add(move);
Console.WriteLine(trainee.net.layers[0]._matrix[0][0]);
generation++;
}
public Trainer(Go game, int generation, string savePath)
{
this.game = game;
this.generation = generation;
this.savePath = savePath;
rng = new Random();
move = new NNet(game.Shape);
if (generation == 0)
{
trainee = new Player(game, Color.White);
}
else
{
trainee = new Player(game, Color.White, savePath + generation + ".dat");
}
opponent = new Player(game, Color.Black);
trainee.CloneTo(opponent);
}
