public static BasicNetwork train(Render render)
{
BasicNetwork network = CreateNetwork(6, 2, 8);
IMLTrain train;
train = new MLMethodGeneticAlgorithm(() =>
{
BasicNetwork result = CreateNetwork(6, 2, 8);
((IMLResettable)result).Reset();
return(result);
}, new Tester(), 2000);
int epoch = 1;
for (int i = 0; i < 80; i++)
{
train.Iteration();
Console.WriteLine(@"Epoch #" + epoch + @" Score:" + train.Error);
epoch++;
if (train.Error >= 37)
{
break;
}
}
return((BasicNetwork)train.Method);
}
public void StartTraining()
{
var Scorer = new GameScore();
var Trainer = new MLMethodGeneticAlgorithm(GetNetwork, Scorer, 200)
{
ThreadCount = 8
};
//Trainer.ThreadCount = 1;
var s = new BestStrategy();
s.Init(Trainer);
Trainer.Strategies.Add(s);
for (int i = 0; i < 1000; i++)
{
Trainer.Iteration();
Console.WriteLine(string.Format("Epoch {0} finished : {1} Hash : {2}", i, Trainer.Genetic.BestGenome.Score, Trainer.Genetic.BestGenome.GetHashCode()));
if ((i % 10) == 0)
{
SaveTrainer(Trainer);
}
}
SaveTrainer(Trainer);
System.IO.File.WriteAllText(@".\Result.txt", Trainer.Genetic.BestGenome.ToString());
}
public BasicNetwork SharkTrain()
{
IMLTrain train = new MLMethodGeneticAlgorithm(() =>
{
BasicNetwork result = CreateNetwork(2, 2);
((IMLResettable)result).Reset();
return(result);
}, new SharkTrainer(), 1000);
for (int i = 0; i < 6; i++)
{
train.Iteration();
Console.WriteLine("Shark Inital Train Score: " + Math.Round(train.Error, 2));
}
return((BasicNetwork)train.Method);
}
