public static int numberOfBatches = 5; //Fixed Update - 50 fps - w 5 klatkach wszystkie sieci neuronowe juz obliczyly wartosci - 10 razy na sekunde wszystkie osobniki moga zmienic kierunek chodzenia
void Start()
{
populationSize = PopulationInputData.populationSize;
populationPartSize = PopulationInputData.populationPartSize;
mutationRate = PopulationInputData.weightsMutationRate;
animalPrefabName = PopulationInputData.animalPrefabName;
startingPosition = PopulationInputData.startingPosition;
speed = PopulationInputData.speed;
physicalMutationRate = PopulationInputData.physicalMutationRate;
timeBelowAveragePenalty = PopulationInputData.timeBelowAveragePenalty;
_newGenerationMove = true;
_currentMGenes = new List <float>();
__animalsToActivate = new List <int>();
bestDistances = new List <float>();
bestFitnesses = new List <float>();
averageDistances = new List <float>();
averageFitnesses = new List <float>();
_animalIndexesToMove = new int[populationPartSize];
_animalsObjects = new List <GameObject>();
_animals = new List <Animal>();
modelAnimal = Instantiate(Resources.Load("Prefabs/" + animalPrefabName) as GameObject);
var movingParts = modelAnimal.GetComponentsInChildren <JointHandler>();
AnimalBrain.noMovingParts = movingParts.Length;
// AnimalBrain.outputSize = AnimalBrain.outputPerArm * AnimalBrain.noMovingParts + AnimalBrain.armsToMoveCount;
AnimalBrain.outputSize = AnimalBrain.outputPerArm * AnimalBrain.noMovingParts;
_iterationsToResetMGenes = (int)Mathf.Ceil(Mathf.Log(populationSize, 2));
modelAnimal.SetActive(false);
if (PopulationInputData.migrationEnabled)
{
LoadMigratedIndividuals();
_migratedAnimalsLeftToPick = migratedAnimals.Count;
_chanceToMigrate = Random.Range(0.0f, 100.0f);
}
CreateGeneration();
_geneticAlgorithm = new GeneticAlgorithm(_animals);
_populationUIhandler = transform.Find("infoCanvas").GetComponent <PopulationUI>();
StartCoroutine("MoveGenerationBatch");
}
public void init()
{
ui = new PopulationUI();
ui.ctrl = this;
ui.init();
}
