private void timer2_Tick(object sender, EventArgs e)
{
timer2.Interval = timer1.Interval;
switch (game.State)
{
case GameState.Ingame:
if (elapsed > timeForGeneration)
{
game.State = GameState.Loss;
}
game.UpdateTime(elapsed, timeForGeneration);
var simulationResult = game.SimulateStep(neat);
game.MoveElements(simulationResult);
game.CheckBallPlayerSCollision();
Invalidate();
elapsed += timer2.Interval;
break;
case GameState.Loss:
genCount++;
label1.Text = "Generation: " + genCount.ToString();
neat.CreateNewGeneration();
//game.RunChampionsAgain(neat.Champions);
Invalidate();
game.State = GameState.Ingame;
game.ResetPositions();
elapsed = 0;
break;
}
}
public void RunSimulation()
{
var results = new List <int>(100);
int generation = 0;
for (int j = 0; j < 100; j++)
{
List <object> players = new List <object>(100);
for (int i = 0; i < 150; i++)
{
players.Add(new Player(i, this));
}
//List<Node> input;
//SortedList<int, Gene> genes;
Random rnd = new Random();
//OptimalGenome(out input, out genes);
//var inp = CreateInputNodes();
var g = new SortedList <int, Gene>(3);
List <Node> nodes = new List <Node>(4);
nodes.Add(new Node(NodeType.Sensor, 0, 0));
nodes.Add(new Node(NodeType.Sensor, 0, 1));
nodes.Add(new Node(NodeType.Sensor, 0, 2));
nodes.Add(new Node(NodeType.Output, 1, 3));
for (int i = 0; i < 3; i++)
{
var gene = new Gene(nodes[i], nodes[3], (float)rnd.NextDouble() * (rnd.Next(0, 10) >= 5 ? 1f : -1f), GeneType.Enabled, i);
g.Add(i, gene);
nodes[i].OutgoingConnections.Add(gene);
}
Neat neat = new Neat(nodes, g, FitnessFunction, players);
neat.SetParameters(c3: 1);
// Neat neat = new Neat(nodes, new SortedList<int, Gene>(), FitnessFunction, players);
// Neat neat = new Neat(input, genes, FitnessFunction, players);
generation = 0;
bestGenome = null;
while (bestGenome == null)
{
first = neat.SimulateStepFromNeat(GetParameters(0));
second = neat.SimulateStepFromNeat(GetParameters(1));
third = neat.SimulateStepFromNeat(GetParameters(2));
fourth = neat.SimulateStepFromNeat(GetParameters(3));
neat.CreateNewGeneration();
generation++;
}
results.Add(generation);
}
StreamWriter sw = new StreamWriter("xor.txt");
sw.WriteLine("XOR results, 100 runs");
sw.WriteLine("how many generation it took for each run:");
int max = 0;
for (int i = 0; i < results.Count; i++)
{
max += results[i];
sw.WriteLine(i + ". run -> " + results[i]);
}
sw.WriteLine("Average generation in a run: " + (double)max / results.Count);
sw.Close();
}
