/// <summary>
/// NOTE: This is entirely copied from PushGP, except EvaluateIndividual
/// was changed to PredictIndividual, as noted below (twice).
/// </summary>
protected internal override PushGPIndividual Autosimplify(PushGPIndividual inIndividual, int steps)
{
PushGPIndividual simplest = (PushGPIndividual)inIndividual.Clone();
PushGPIndividual trial = (PushGPIndividual)inIndividual.Clone();
PredictIndividual(simplest, true);
// Changed from EvaluateIndividual
float bestError = simplest.GetFitness();
bool madeSimpler = false;
for (int i = 0; i < steps; i++)
{
madeSimpler = false;
float method = Rng.Next(100);
if (trial._program.ProgramSize() <= 0)
{
break;
}
if (method < _simplifyFlattenPercent)
{
// Flatten random thing
int pointIndex = Rng.Next(trial._program.ProgramSize());
object point = trial._program.Subtree(pointIndex);
if (point is Program)
{
trial._program.Flatten(pointIndex);
madeSimpler = true;
}
}
else
{
// Remove small number of random things
int numberToRemove = Rng.Next(3) + 1;
for (int j = 0; j < numberToRemove; j++)
{
int trialSize = trial._program.ProgramSize();
if (trialSize > 0)
{
int pointIndex = Rng.Next(trialSize);
trial._program.ReplaceSubtree(pointIndex, new Program());
trial._program.Flatten(pointIndex);
madeSimpler = true;
}
}
}
if (madeSimpler)
{
PredictIndividual(trial, true);
// Changed from EvaluateIndividual
if (trial.GetFitness() <= bestError)
{
simplest = (PushGPIndividual)trial.Clone();
bestError = trial.GetFitness();
}
}
trial = (PushGPIndividual)simplest.Clone();
}
return(simplest);
}
/// <summary>
/// This must be private, since there must be a _solutionGA set before this
/// method is invoked.
/// </summary>
/// <remarks>
/// This must be private, since there must be a _solutionGA set before this
/// method is invoked. Use SetGAandTrainers() instead.
/// </remarks>
private void InitTrainerPopulation()
{
_trainerPopulation = new List <PushGPIndividual>();
PushGPIndividual individual = new PushGPIndividual();
for (int i = 0; i < _trainerPopulationSize; i++)
{
_trainerPopulation.Add((PushGPIndividual)individual.Clone());
_solutionGA.InitIndividual(_trainerPopulation[i]);
}
EvaluateTrainerFitnesses();
}