private void repartirOrdenes()
{
try
{
GeneticAlgorithm a = new GeneticAlgorithm(agents, requestedServices);
agente.hablar("Espera mientras resuelvo el problema");
a.CreateInitialPopulation();
a.CalculateFitnessGenes();
for (int i = 0; i < a.GenerationsNumber; i++)
{
a.CreateNextGeneration();
a.CalculateFitnessGenes();
}
Console.WriteLine(a.BestGenByGeneration());
formResultado = new Form2();
formResultado.Show();
formResultado.cargarGen(a);
agente.hablar("Así se debe repartir las órdenes");
}
catch (Exception ex)
{
agente.hablar("Debe cargar los agentes y órdenes primero");
}
}
public AICharacter[] NextGen(AICharacter[] population)
{
#region END GEN
int name = 0;
var maxFitness = 0;
// GET MAX SCORE
for (int i = 0; i < population.Length; i++)
{
var fitness = (double)(population[i].GetScore() + 1);
if (fitness > maxFitness)
{
name = i;
maxFitness = (int)fitness;
}
}
// CALCULATE FITNESS
for (int i = 0; i < population.Length; i++)
{
var skipperScore = (double)(population[i].GetScore() + 1);
population[i].brain.Fitness = skipperScore / maxFitness;
}
// SAVE BEST GENOME
if (maxFitness > prevMaxFitness)
{
SaveGenome(maxFitness, population[name].brain.genome);
prevMaxFitness = maxFitness;
}
#endregion
// NEW GEN
#region NEW GEN
brainArr.Clear();
// RETRIEVE BRAINS!
for (int i = 0; i < population.Length; i++)
{
brainArr.Add(population[i].brain);
}
// GENERATE NEXT GEN GENES!
var nextGenBrainArr = geneticAlgorithm.CreateNextGeneration(brainArr);
// SET CURRENT GENES
for (int i = 0; i < nextGenBrainArr.Count; i++)
{
population[i].SetGenes(nextGenBrainArr[i].Genes());
}
#endregion
return(population);
}
