ResetAndKill()
{
m_dTotFitAdj = 0;
m_dAvFitAdj = 0;
// Purge the species that doesn't improve
for (int i = m_vecSpecies.Count - 1; i >= 0; i--)
{
CSpecies species = m_vecSpecies[i];
species.Purge();
if (species.GensNoImprovement() >
_params.NumGensAllowedNoImprovement &&
species.BestFitness() < m_dBestEverFitness)
{
m_vecSpecies.RemoveAt(i);
Debug.Log("killed species " + species.ID());
}
}
for (int i = 0; i < m_Population.Count; i++)
{
CGenome genome = m_Population[i];
genome.DeletePhenotype();
}
}
Epoch(Dictionary <int, float> fitnessScores)
{
if (fitnessScores.Count != m_Population.Count)
{
Debug.LogError("scores and genomes mismatch error. (" + fitnessScores.Count + " / " + m_Population.Count + ")");
return(null);
}
ResetAndKill();
for (int i = 0; i < m_Population.Count; i++)
{
CGenome genome = m_Population[i];
genome.SetFitness(fitnessScores[genome.ID()]);
}
SortAndRecord();
SpeciateGenomes();
CalculateSpawnLevels();
Debug.Log("best fitness last gen: " + m_Population[0].Fitness());
List <CGenome> newPopulation = new List <CGenome> ();
int numSpawned = SpawnLeaders(newPopulation);
for (int i = 0; i < m_vecSpecies.Count; i++)
{
CSpecies species = m_vecSpecies[i];
numSpawned = SpawnOffspring(species, numSpawned, newPopulation);
}
/*
* Tournament selection is used over the entire population if due
* to a underflow of the species amount to spawn the offspring
* doesn't fill the entire population additional children needs to
* created.
*/
if (numSpawned < _params.NumGenomesToSpawn)
{
int numMoreToSpawn = _params.NumGenomesToSpawn - numSpawned;
while (numMoreToSpawn-- > 0)
{
CGenome baby = new CGenome(TournamentSelection(m_PopSize / 5));
baby.SetID(++nextGenomeID);
newPopulation.Add(baby);
}
}
m_Population = newPopulation;
m_iGeneration++;
return(CreatePhenotypes());
}
SpawnLeaders(List <CGenome> newPopulation)
{
for (int i = 0; i < m_vecSpecies.Count; i++)
{
CSpecies species = m_vecSpecies[i];
CGenome baby = species.Leader();
Debug.Log("spawning leader (" + baby.Fitness() + "): " + baby.ID() + " for " + species.ID());
newPopulation.Add(baby);
}
return(newPopulation.Count);
}
CalculateSpawnLevels()
{
for (int i = 0; i < m_Population.Count; i++)
{
CGenome genome = m_Population[i];
float toSpawn = 0;
if (m_dAvFitAdj > 0)
{
toSpawn = genome.GetAdjustedFitness() / m_dAvFitAdj;
}
genome.SetAmountToSpawn(toSpawn);
}
for (int i = 0; i < m_vecSpecies.Count; i++)
{
CSpecies species = m_vecSpecies[i];
species.CalculateSpawnAmount();
}
}
SpawnOffspring(CSpecies species, int numSpawned,
List <CGenome> newPopulation)
{
CGenome baby = null;
/*
* Prevent overflowing the total number of genomes spawned per population.
*/
if (numSpawned < _params.NumGenomesToSpawn)
{
// Exclude the leader from numToSpawn.
int numToSpawn = Mathf.RoundToInt(species.NumToSpawn()) - 1;
numToSpawn = Mathf.Min(numToSpawn, _params.NumGenomesToSpawn - numSpawned);
Debug.Log("spawning " + numToSpawn + " num indivudals for species " + species.ID() + ", best fitness: " + species.BestFitness());
while (numToSpawn-- > 0)
{
/*
* Unless we have >2 members in the species crossover
* can't be performed.
*/
if (species.NumMembers() == 1)
{
baby = new CGenome(species.Spawn());
}
else
{
CGenome mum = species.Spawn();
if (Random.value < _params.CrossoverRate)
{
CGenome dad = species.Spawn();
int numAttempts = 5;
// try to select a genome which is not the same as mum
while (mum.ID() == dad.ID() && numAttempts-- > 0)
{
dad = species.Spawn();
}
if (mum.ID() != dad.ID())
{
baby = Crossover(mum, dad);
}
else
{
if (Random.value < 0.5f)
{
baby = new CGenome(dad);
}
else
{
baby = new CGenome(mum);
}
}
}
else
{
baby = new CGenome(mum);
}
}
if (baby == null)
{
continue;
}
baby.SetID(++nextGenomeID);
MutateBaby(baby); //EDIT me
baby.SortGenes();
newPopulation.Add(baby);
if (numSpawned++ >= _params.NumGenomesToSpawn)
{
numToSpawn = 0;
break;
}
}
}
return(numSpawned);
}
SpeciateGenomes()
{
bool addedToSpecies = false;
for (int i = 0; i < m_Population.Count; i++)
{
CGenome genome = m_Population[i];
float bestCompatability = 1000;
CSpecies bestSpecies = null;
for (int j = 0; j < m_vecSpecies.Count; j++)
{
CSpecies species = m_vecSpecies[j];
float compatibility = genome.GetCompatibilityScore(species.Leader());
// if this individual is similar to this species leader add to species
if (compatibility < bestCompatability)
{
bestCompatability = compatibility;
bestSpecies = species;
}
}
if (bestCompatability <= _params.CompatibilityThreshold)
{
bestSpecies.AddMember(genome);
genome.SetSpecies(bestSpecies.ID());
addedToSpecies = true;
}
if (!addedToSpecies)
{
// we have not found a compatible species so a new one will be created
m_vecSpecies.Add(new CSpecies(genome, nextSpeciesID++));
}
addedToSpecies = false;
}
/*
* Adjust the fitness for all members of the every species to take
* into account fitness sharing and age of species.
*/
for (int i = 0; i < m_vecSpecies.Count; i++)
{
CSpecies species = m_vecSpecies[i];
species.AdjustFitnesses();
}
/*
* Calculate new adjusted total and average fitness for the population.
*/
for (int i = 0; i < m_Population.Count; i++)
{
CGenome genome = m_Population[i];
m_dTotFitAdj += genome.GetAdjustedFitness();
}
m_dAvFitAdj = m_dTotFitAdj / m_Population.Count;
}