static void Main(string[] args)
{
IndividualController _individualController = new IndividualController();
if (args.Length == 0)
{
Constants.Target = "Created by Alguek";
}
else
{
Constants.Target = args[0];
}
// Geração atual
// Current generation
int generation = 0;
List <Individual> population = new List <Individual>();
bool found = false;
// Cria população inicial
// Create initial population
for (int i = 0; i < Constants.POPULATION_SIZE; i++)
{
string gnome = _individualController.CreateGnome();
population.Add(new Individual(gnome));
}
while (!found)
{
// Ordena a população na ordem da Accuracy
// Sort the population by the order of Accuracy score
population = population.OrderByDescending(x => x.Accuracy).ToList();
// Se o individual tem mais Accuracy do que o Target
// significa que ele achou a melhor resposta
// e o programa vai parar
// if the individual having highness Accuracy score ie.
// target size then we know that we have reached to the target
// and break the loop
if (population[0].Accuracy >= Constants.Target.Length)
{
found = true;
break;
}
// Caso contrario cria uma nova geração de filhos
// Otherwise generate new offsprings for new generation
List <Individual> new_generation = new List <Individual>();
// Pega apenas os melhores, apenas os 10% filhos com mais Accuracy da geração anterior
// vai para a nova geração
// Perform Elitism, that mean 10% of fittest population
// goes to the next generation
int s = (10 * Constants.POPULATION_SIZE) / 100;
new_generation = population.GetRange(0, s);
// Os 50% melhores da population vão dar "mate"
// e criar novos filhos
// From 50% of fittest population, Individuals
// will mate to produce offspring
s = (90 * Constants.POPULATION_SIZE) / 100;
for (int i = 0; i < s; i++)
{
int r1 = new Random((int)DateTime.Now.Ticks & 0x0000FFFF).Next(0, 50);
int r2 = new Random((int)DateTime.Now.Ticks & 0x0000FFFF).Next(0, 50);
Individual parent1 = population[r1];
Individual parent2 = population[r2];
Individual offspring = _individualController.Mate(parent1, parent2);
new_generation.Add(offspring);
}
population = new_generation;
Console.WriteLine("Generation: " + generation + "\t");
Console.WriteLine("String: " + population[0].Chromosome + "\t");
Console.WriteLine("Fitness: " + population[0].Accuracy + "\t \n");
generation++;
}
Console.WriteLine("Generation: " + generation + "\t");
Console.WriteLine("String: " + population[0].Chromosome + "\t");
Console.WriteLine("Fitness: " + population[0].Accuracy + "\t");
}
