public virtual LGPProgram Clone()
{
LGPProgram clone = new LGPProgram(mPop, mOperatorSet.Clone());
clone.Copy(this);
return(clone);
}
public virtual LGPProgram CreateProgram(int size, LGPEnvironment env)
{
LGPProgram program = new LGPProgram(this, mOperatorSet.Clone());
program.Create(size);
return(program);
}
public virtual void BreedInitialPopulation()
{
Setup();
int iPopulationSize = mConfig.PopulationSize;
mPopInitInstructionFactory.Initialize(this);
EvaluateFitness();
mGlobalBestProgram = FindFittestProgramInCurrentGeneration().Clone();
}
public static void Shuffle(IList <LGPProgram> list)
{
Random rng = new Random();
int n = list.Count;
while (n > 1)
{
n--;
int k = rng.Next(n + 1);
LGPProgram value = list[k];
list[k] = list[n];
list[n] = value;
}
}
public void Replace(LGPProgram weak_program_in_current_pop, LGPProgram child_program)
{
//bool found = false;
for (int i = 0; i < mPrograms.Count; ++i)
{
if (mPrograms[i] == weak_program_in_current_pop)
{
//found = true;
mPrograms[i] = child_program;
}
}
//if (found == false)
//{
// throw new Exception();
//}
}
public void Copy(LGPProgram rhs)
{
mSetup = rhs.mSetup;
mFitness = rhs.mFitness;
mObjectiveValue = rhs.mObjectiveValue;
mIsFitnessValid = rhs.mIsFitnessValid;
mRegisterSet = rhs.mRegisterSet.Clone();
mOperatorSet = rhs.mOperatorSet.Clone();
mConstantSet = rhs.mConstantSet.Clone();
mPop = rhs.mPop;
for (int i = 0; i < rhs.mInstructions.Count; ++i)
{
mInstructions.Add(rhs.mInstructions[i].Clone());
mInstructions[i].Program = this;
}
}
public bool IsBetterThan(LGPProgram rhs)
{
return(mFitness > rhs.Fitness);
}
public void AddProgram(LGPProgram lgp)
{
mPrograms.Add(lgp);
}
public virtual void InitializeProgramRegisters(LGPProgram lgp, LGPFitnessCase fitness_case)
{
mRegInitInstructionFactory.InitializeRegisters(lgp.RegisterSet, lgp.ConstantSet, fitness_case);
}
public virtual void Evolve()
{
int iPopSize = this.mConfig.PopulationSize;
int program_count = 0;
while (program_count < iPopSize)
{
KeyValuePair <LGPProgram, LGPProgram> tournament_winners = new KeyValuePair <LGPProgram, LGPProgram>();
KeyValuePair <LGPProgram, LGPProgram> tournament_losers = new KeyValuePair <LGPProgram, LGPProgram>();
mReproductionSelectionInstructionFactory.Select(this, ref tournament_winners, ref tournament_losers);
LGPProgram tp1 = tournament_winners.Key.Clone();
LGPProgram tp2 = tournament_winners.Value.Clone();
double r = DistributionModel.GetUniform();
if (r < this.mConfig.CrossoverRate)
{
mCrossoverInstructionFactory.Crossover(this, tp1, tp2);
}
r = DistributionModel.GetUniform();
if (r < this.mConfig.MacroMutationRate)
{
mMutationInstructionFactory.Mutate(this, tp1);
}
r = DistributionModel.GetUniform();
if (r < this.mConfig.MacroMutationRate)
{
mMutationInstructionFactory.Mutate(this, tp2);
}
r = DistributionModel.GetUniform();
if (r < this.mConfig.MicroMutationRate)
{
tp1.MicroMutate(mGaussian);
}
r = DistributionModel.GetUniform();
if (r < this.mConfig.MicroMutationRate)
{
tp2.MicroMutate(mGaussian);
}
if (!tp1.IsFitnessValid)
{
tp1.EvaluateFitness();
}
if (!tp2.IsFitnessValid)
{
tp2.EvaluateFitness();
}
if (tp1.IsBetterThan(tp2))
{
if (tp1.IsBetterThan(mGlobalBestProgram))
{
mGlobalBestProgram = tp1.Clone();
}
}
else
{
if (tp2.IsBetterThan(mGlobalBestProgram))
{
mGlobalBestProgram = tp2.Clone();
}
}
LGPProgram loser1 = mSurvivalInstructionFactory.Compete(this, tournament_losers.Key, tp1); // this method returns the pointer to the loser in the competition for survival;
LGPProgram loser2 = mSurvivalInstructionFactory.Compete(this, tournament_losers.Value, tp2);
if (loser1 == tournament_losers.Key)
{
++program_count;
}
if (loser2 == tournament_losers.Value)
{
++program_count;
}
}
mCurrentGeneration++;
}
public LGPInstruction(LGPProgram prog)
{
mProgram = prog;
}