private static void initializeGeneticAlgorithm(
int populationSize,
int parentalChromosomesSurviveCount,
OptimizableNeuralNetwork baseNeuralNetwork)
{
Population <OptimizableNeuralNetwork> brains = new Population <OptimizableNeuralNetwork>();
for (int i = 0; i < (populationSize - 1); i++)
{
if (baseNeuralNetwork == null)
{
brains.Add(NeuralNetworkDrivenAgent.randomNeuralNetworkBrain());
}
else
{
brains.Add(baseNeuralNetwork.Mutate());
}
}
if (baseNeuralNetwork != null)
{
brains.Add(baseNeuralNetwork);
}
else
{
brains.Add(NeuralNetworkDrivenAgent.randomNeuralNetworkBrain());
}
ga = new GeneticAlgorithm <OptimizableNeuralNetwork, double>(brains, TournamentEnvironmentFitness.Calculate);
ga.ParentChromosomesSurviveCount = parentalChromosomesSurviveCount;
}
private void MenuItem_Click(object sender, RoutedEventArgs e)
{
var rx = Rnd.NextDouble();
var ry = Rnd.NextDouble();
var ra = Rnd.NextDouble();
var agent = new NeuralNetworkDrivenAgent(rx, ry, ra);
environment.Add(agent);
Agents.Add(new ConsumerPresenter(agent)
{
X = 1000.0 * rx, Y = 1000.0 * ry, Angle = 360.0 * ra
});
}
public MainWindow()
{
InitializeComponent();
Agents = new ObservableCollection <AgentPresenter>();
initializeGeneticAlgorithm(5, 1, null);
const int w = 600;
const int h = 400;
environment = new AgentsEnvironment(w, h);
environment.AgentEvent += new RenderObserver(this).notify;
NeuralNetwork brain = ga.GetBest();
for (int i = 0; i < 15; i++)
{
int x = Rnd.Next(w);
int y = Rnd.Next(h);
double direction = Rnd.NextDouble() * 2 * Math.PI;
NeuralNetworkDrivenAgent agent = new NeuralNetworkDrivenAgent(x, y, direction);
agent.setBrain(brain);
Agents.Add(new ConsumerPresenter(agent));
environment.Add(agent);
}
for (int i = 0; i < 10; i++)
{
Food food = createRandomFood(w, h);
environment.Add(food);
Agents.Add(new FoodPresenter(food));
}
new Thread(() =>
{
while (true)
{
try
{
Thread.Sleep(50);
if (play)
{
environment.timeStep();
Dispatcher.Invoke(() =>
{
foreach (var pres in Agents)
{
pres.X = pres.agent.X * 1000 / w;
pres.Y = pres.agent.Y * 1000 / h;
var cons = pres as ConsumerPresenter;
if (cons != null)
{
cons.Angle = (cons.agent as NeuralNetworkDrivenAgent).Angle * 180 / Math.PI;
}
}
});
}
}
catch { break; }
}
}).Start();
}
