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;
}
public static OptimizableNeuralNetwork randomNeuralNetworkBrain()
{
OptimizableNeuralNetwork nn = new OptimizableNeuralNetwork(15);
for (int i = 0; i < 15; i++)
{
var f = ThresholdFunction.Random();
nn.SetNeuronFunction(i, f, ThresholdFunction.GetDefaultParams(f));
}
for (int i = 0; i < 6; i++)
{
nn.SetNeuronFunction(i, ThresholdFunction.Function.Linear, ThresholdFunction.GetDefaultParams(ThresholdFunction.Function.Linear));
}
for (int i = 0; i < 6; i++)
{
for (int j = 6; j < 15; j++)
{
nn.AddLink(i, j, random.NextDouble());
}
}
for (int i = 6; i < 15; i++)
{
for (int j = 6; j < 15; j++)
{
if (i < j)
{
nn.AddLink(i, j, random.NextDouble());
}
}
}
return(nn);
}
public static double Calculate(OptimizableNeuralNetwork chromosome)
{
// TODO maybe, its better to initialize these parameters in constructor
const int width = 200;
const int height = 200;
int agentsCount = 10;
int foodCount = 5;
int environmentIterations = 50;
AgentsEnvironment env = new AgentsEnvironment(width, height);
for (int i = 0; i < agentsCount; i++)
{
int x = random.Next(width);
int y = random.Next(height);
double direction = 2 * Math.PI * random.NextDouble();
NeuralNetworkDrivenAgent agent = new NeuralNetworkDrivenAgent(x, y, direction);
agent.setBrain(chromosome.Clone() as NeuralNetwork);
env.Add(agent);
}
for (int i = 0; i < foodCount; i++)
{
Food food = newPieceOfFood(width, height);
env.Add(food);
}
EatenFoodObserver tournamentListener = new FitnessObserver(width, height);
env.AgentEvent += tournamentListener.notify;
for (int i = 0; i < environmentIterations; i++)
{
env.timeStep();
}
double score = tournamentListener.getScore();
return(1.0 / score);
}
