public void NextGeneration(string userSelection = "")
{
//should i save each generation in the population object
//targetstring is blank (if selection type is user, don't need a target eh?
//make genome more generic, and specifiable
//currently the targetstring is defining the length of the seeded genomes. That's not ideal.
//I should specify the seeding information in the encoder....
//how do I deal with variable length genomes???? This matters in crossover, fitness, and seeding the population
//for the next step only need to focus on crossover and seeding.
//need to be able to seed a population from a list of values
//stop using all the letters a - z?
if (!(_selection._selectionType == "god mode"))
{
_fitness.Apply(Population);
}
List <Genome> parentSelection = _selection.Select(Population, userSelection);
_crossover.Apply(Population, parentSelection);
_mutation.Apply(Population);
Population._generation++;
Debug.Log(this.ToString());
}
public void NextGeneration()
{
var popOrderedByFitness = _fitness.Apply(Population);
var parentSelection = _selection.Select(Population);
var childrenCrossed = _crossover.Apply(popOrderedByFitness, parentSelection);
var childrenMutated = _mutation.Apply(childrenCrossed);
Population = childrenMutated;
Population._generation++;
}
public void NextGeneration(string userSelection = "")
{
//only apply the fitness class if selection type is fitness based
if (!(_selection._selectionType == "god mode"))
{
_fitness.Apply(Population);
}
List <Genome> parentSelection = _selection.Select(Population, userSelection); //applies the selection algorithm chosen to the population
_crossover.Apply(Population, parentSelection);
_mutation.Apply(Population);
Population._generation++;
Debug.Log(this);
}
