public ga(int _populationSize, int chromosomeLength, Dictionary<byte, float> _codex)
{
populationSize = _populationSize;
codex = _codex;
thisProb.Add(new KeyValuePair<object, float>(true, .35f));
thisProb.Add(new KeyValuePair<object, float>(false, .65f));
probGen = new ProbGen(thisProb);
for (int i = 0; i < populationSize; i++) {
population.Add(new chromosome(chromosomeLength, this));
}
}
private void CyclePopulation()
{
List<KeyValuePair<object, float>> fitnessProbList = new List<KeyValuePair<object, float>>();
float magnitude = 0;
foreach(chromosome chr in population) {
magnitude += chr.fitness;
}
for(int k = 0; k < population.Count-1; k++) {
fitnessProbList.Add(new KeyValuePair<object, float>(k, population[k].fitness-1 / magnitude));
}
ProbGen fitnessProb = new ProbGen(fitnessProbList);
for (int i = 0; i < population.Count-1; i++) {
chromosome thisChr = population[i];
chromosome partner = population[(int)fitnessProb.next()];
for(int j = 0; j < thisChr.genes.Count; j++) {
if(Random.value > .5f) {
thisChr.genes[j] = partner.genes[j];
}
}
population[i] = thisChr;
}
}
