public void CreateGen()
{
List <Pig.Player> newPlayers = new List <Pig.Player>();
foreach (Pig.Player player in Players)
{
player.averageFitness = player.totalFitness / player.gameCount;
}
Players.Sort((a, b) => b.averageFitness.CompareTo(a.averageFitness));
double totalSqrtFitness = 0;
totalSqrtFitness = Players.Sum(x => Math.Pow(x.averageFitness, genPlayerFitScale));
maxFitness = Players[0].averageFitness;
newPlayers.Add(new Pig.Player(Players[0]));
newPlayers.Add(new Pig.Player(Players[1]));
newPlayers.Add(new Pig.Player(Players[2]));
for (int i = 3; i < Players.Count; i++)
{
Pig.Player cross1 = GetRandomMember(totalSqrtFitness);
//Pig.Player cross2 = GetRandomMember(totalSqrtFitness - Math.Pow(cross1.averageFitness, genPlayerFitScale), cross1);
Pig.Player cross2 = GetRandomMember(totalSqrtFitness);
Pig.Player newPlayer = new Pig.Player(cross1, cross2);
newPlayer.Mutate();
newPlayers.Add(newPlayer);
}
Players = newPlayers; //copy over new players
}
public void CreateGen()
{
List <Pig.Player> newPlayers = new List <Pig.Player>();
foreach (Pig.Player player in Players)
{
player.averageFitness = player.totalFitness / player.gameCount;
}
Players.Sort((a, b) => b.averageFitness.CompareTo(a.averageFitness));
double totalSqrtFitness = 0;
totalSqrtFitness = Players.Sum(x => Math.Pow(x.averageFitness, genPlayerFitScale));
maxFitness = Players[0].averageFitness;
for (int i = 0; i < 6; i++)
{
newPlayers.Add(new Pig.Player(Players[i]));
}
//using (var stringwriter = new System.IO.StringWriter())
//{
// Type[] types = new Type[3];
// types[0] = typeof(NN.NeuralNet);
// types[1] = typeof(NN.Neuron);
// types[2] = typeof(NN.Layer);
// var serializer = new XmlSerializer(Players[0].GetType(), types);
// serializer.Serialize(stringwriter, Players[0]);
// File.WriteAllText("bestPlayer.dat", stringwriter.ToString());
//}
for (int i = 6; i < Players.Count; i++)
{
Pig.Player cross1 = GetRandomMember(totalSqrtFitness);
//Pig.Player cross2 = GetRandomMember(totalSqrtFitness - Math.Pow(cross1.averageFitness, genPlayerFitScale), cross1);
Pig.Player cross2 = GetRandomMember(totalSqrtFitness);
Pig.Player newPlayer = new Pig.Player(cross1, cross2);
newPlayer.Mutate(Constants.mutationRate, Constants.percentMutate);
newPlayers.Add(newPlayer);
}
Players = newPlayers; //copy over new players
//foreach (Pig.Player player in Players)
//{
// player.net._outputLayer._neurons[0]._weights[0] = 0;
// player.net._outputLayer._neurons[0]._weights[1] = 1;
//}
}