private List <NeatGenome <T> > CreateOffspring(
Species <T>[] speciesArr,
DiscreteDistribution speciesDist,
DiscreteDistribution[] genomeDistArr,
double interspeciesMatingProportion,
IRandomSource rng)
{
// Calc total number of offspring to produce for the population as a whole.
int offspringCount = speciesArr.Sum(x => x.Stats.OffspringCount);
// Create an empty list to add the offspring to (with preallocated storage).
var offspringList = new List <NeatGenome <T> >(offspringCount);
// Loop the species.
for (int speciesIdx = 0; speciesIdx < speciesArr.Length; speciesIdx++)
{
// Get the current species.
Species <T> species = speciesArr[speciesIdx];
// Get the DiscreteDistribution for genome selection within the current species.
DiscreteDistribution genomeDist = genomeDistArr[speciesIdx];
// Determine how many offspring to create through asexual and sexual reproduction.
SpeciesStats stats = species.Stats;
int offspringCountAsexual = stats.OffspringAsexualCount;
int offspringCountSexual = stats.OffspringSexualCount;
// Special case: A species with a single genome marked for selection, cannot perform intra-species sexual reproduction.
if (species.Stats.SelectionSizeInt == 1)
{
// Note. here we assign all the sexual reproduction allocation to asexual reproduction. In principle
// we could still perform inter species sexual reproduction, but that complicates the code further
// for minimal gain.
offspringCountAsexual += offspringCountSexual;
offspringCountSexual = 0;
}
// Create a copy of speciesDist with the current species removed from the set of possibilities.
// Note. The remaining probabilities are normalised to sum to one.
DiscreteDistribution speciesDistUpdated = speciesDist.RemoveOutcome(speciesIdx);
// Create offspring from the current species.
CreateSpeciesOffspringAsexual(
species, genomeDist, offspringCountAsexual, offspringList, rng);
CreateSpeciesOffspringSexual(
speciesArr, species, speciesDistUpdated,
genomeDistArr, genomeDist,
offspringCountSexual, offspringList,
interspeciesMatingProportion, rng);
}
return(offspringList);
}
private NeatGenome <T> Create(
NeatGenome <T> parent,
IRandomSource rng,
ref DiscreteDistribution mutationTypeDist)
{
// Determine the type of mutation to attempt.
MutationType mutationTypeId = (MutationType)DiscreteDistribution.Sample(rng, mutationTypeDist);
// Attempt to create a child genome using the selected mutation type.
NeatGenome <T> childGenome = null;
switch (mutationTypeId)
{
// Note. These subroutines will return null if they cannot produce a child genome,
// e.g. 'delete connection' will not succeed if there is only one connection.
case MutationType.ConnectionWeight:
childGenome = _mutateWeightsStrategy.CreateChildGenome(parent, rng);
break;
case MutationType.AddNode:
// FIXME: Reinstate.
childGenome = _addNodeStrategy.CreateChildGenome(parent, rng);
break;
case MutationType.AddConnection:
childGenome = _addConnectionStrategy.CreateChildGenome(parent, rng);
break;
case MutationType.DeleteConnection:
childGenome = _deleteConnectionStrategy.CreateChildGenome(parent, rng);
break;
default:
throw new Exception($"Unexpected mutationTypeId [{mutationTypeId}].");
}
if (null != childGenome)
{
return(childGenome);
}
// The chosen mutation type was not possible; remove that type from the set of possible types.
mutationTypeDist = mutationTypeDist.RemoveOutcome((int)mutationTypeId);
// Sanity test.
if (0 == mutationTypeDist.Probabilities.Length)
{ // This shouldn't be possible, hence this is an exceptional circumstance.
// Note. Connection weight and 'add node' mutations should always be possible, because there should
// always be at least one connection.
throw new Exception("All types of genome mutation failed.");
}
return(null);
}
/// <summary>
/// Cross specie mating.
/// </summary>
/// <param name="dist">DiscreteDistribution for selecting genomes in the current specie.</param>
/// <param name="distArr">Array of DiscreteDistribution objects for genome selection. One for each specie.</param>
/// <param name="rwlSpecies">DiscreteDistribution for selecting species. Based on relative fitness of species.</param>
/// <param name="currentSpecieIdx">Current specie's index in _specieList</param>
/// <param name="genomeList">Current specie's genome list.</param>
private TGenome CreateOffspring_CrossSpecieMating(DiscreteDistribution dist,
DiscreteDistribution[] distArr,
DiscreteDistribution rwlSpecies,
int currentSpecieIdx,
IList<TGenome> genomeList)
{
// Select parent from current specie.
int parent1Idx = dist.Sample();
// Select specie other than current one for 2nd parent genome.
DiscreteDistribution distSpeciesTmp = rwlSpecies.RemoveOutcome(currentSpecieIdx);
int specie2Idx = distSpeciesTmp.Sample();
// Select a parent genome from the second specie.
int parent2Idx = distArr[specie2Idx].Sample();
// Get the two parents to mate.
TGenome parent1 = genomeList[parent1Idx];
TGenome parent2 = _specieList[specie2Idx].GenomeList[parent2Idx];
return parent1.CreateOffspring(parent2, _currentGeneration);
}
private void CreateSpeciesOffspringSexual(
Species <T>[] speciesArr,
Species <T> species,
DiscreteDistribution speciesDistUpdated,
DiscreteDistribution?[] genomeDistArr,
DiscreteDistribution genomeDist,
int offspringCount,
List <NeatGenome <T> > offspringList,
double interspeciesMatingProportion,
IRandomSource rng,
out int offspringInterspeciesCount)
{
// Calc the number of offspring to create via inter-species sexual reproduction.
int offspringCountSexualInter;
if (interspeciesMatingProportion == 0.0)
{
offspringInterspeciesCount = offspringCountSexualInter = 0;
}
else
{
offspringInterspeciesCount = offspringCountSexualInter = (int)NumericsUtils.ProbabilisticRound(interspeciesMatingProportion * offspringCount, rng);
}
// Calc the number of offspring to create via intra-species sexual reproduction.
int offspringCountSexualIntra = offspringCount - offspringCountSexualInter;
// Get genome list for the current species.
var genomeList = species.GenomeList;
// Produce the required number of offspring from intra-species sexual reproduction.
for (int i = 0; i < offspringCountSexualIntra; i++)
{
// Select/sample parent A from the species.
int genomeIdx = DiscreteDistribution.Sample(rng, genomeDist);
var parentGenomeA = genomeList[genomeIdx];
// Create a new distribution with parent A removed from the set of possibilities.
DiscreteDistribution genomeDistUpdated = genomeDist.RemoveOutcome(genomeIdx);
// Select/sample parent B from the species.
genomeIdx = DiscreteDistribution.Sample(rng, genomeDistUpdated);
var parentGenomeB = genomeList[genomeIdx];
// Create a child genome and add it to offspringList.
var childGenome = _reproductionSexual.CreateGenome(parentGenomeA, parentGenomeB, rng);
offspringList.Add(childGenome);
}
// Produce the required number of offspring from inter-species sexual reproduction.
for (int i = 0; i < offspringCountSexualInter; i++)
{
// Select/sample parent A from the current species.
int genomeIdx = DiscreteDistribution.Sample(rng, genomeDist);
var parentGenomeA = genomeList[genomeIdx];
// Select another species to select parent B from.
int speciesIdx = DiscreteDistribution.Sample(rng, speciesDistUpdated);
Species <T> speciesB = speciesArr[speciesIdx];
// Select parent B from species B.
DiscreteDistribution genomeDistB = genomeDistArr[speciesIdx] !;
genomeIdx = DiscreteDistribution.Sample(rng, genomeDistB);
var parentGenomeB = speciesB.GenomeList[genomeIdx];
// Ensure parentA is the fittest of the two parents.
if (_fitnessComparer.Compare(parentGenomeA.FitnessInfo, parentGenomeB.FitnessInfo) < 0)
{
VariableUtils.Swap(ref parentGenomeA !, ref parentGenomeB !);
}
// Create a child genome and add it to offspringList.
var childGenome = _reproductionSexual.CreateGenome(parentGenomeA, parentGenomeB, rng);
offspringList.Add(childGenome);
}
}
/// <summary>
/// Create the required number of offspring genomes, using specieStatsArr as the basis for selecting how
/// many offspring are produced from each species.
/// </summary>
private List <TGenome> CreateOffspring(SpecieStats[] specieStatsArr, int offspringCount)
{
// Build a DiscreteDistribution for selecting species for cross-species reproduction.
// While we're in the loop we also pre-build a DiscreteDistribution for each specie;
// Doing this before the main loop means we have DiscreteDistributions available for
// all species when performing cross-specie matings.
int specieCount = specieStatsArr.Length;
double[] specieFitnessArr = new double[specieCount];
DiscreteDistribution[] distArr = new DiscreteDistribution[specieCount];
// Count of species with non-zero selection size.
// If this is exactly 1 then we skip inter-species mating. One is a special case because for 0 the
// species all get an even chance of selection, and for >1 we can just select normally.
int nonZeroSpecieCount = 0;
for (int i = 0; i < specieCount; i++)
{
// Array of probabilities for specie selection. Note that some of these probabilities can be zero, but at least one of them won't be.
SpecieStats inst = specieStatsArr[i];
specieFitnessArr[i] = inst._selectionSizeInt;
if (0 == inst._selectionSizeInt)
{
// Skip building a DiscreteDistribution for species that won't be selected from.
distArr[i] = null;
continue;
}
nonZeroSpecieCount++;
// For each specie we build a DiscreteDistribution for genome selection within
// that specie. Fitter genomes have higher probability of selection.
List <TGenome> genomeList = _specieList[i].GenomeList;
double[] probabilities = new double[inst._selectionSizeInt];
for (int j = 0; j < inst._selectionSizeInt; j++)
{
probabilities[j] = genomeList[j].EvaluationInfo.Fitness;
}
distArr[i] = new DiscreteDistribution(probabilities);
}
// Complete construction of DiscreteDistribution for specie selection.
DiscreteDistribution rwlSpecies = new DiscreteDistribution(specieFitnessArr);
// Produce offspring from each specie in turn and store them in offspringList.
List <TGenome> offspringList = new List <TGenome>(offspringCount);
for (int specieIdx = 0; specieIdx < specieCount; specieIdx++)
{
SpecieStats inst = specieStatsArr[specieIdx];
List <TGenome> genomeList = _specieList[specieIdx].GenomeList;
// Get DiscreteDistribution for genome selection.
DiscreteDistribution dist = distArr[specieIdx];
// --- Produce the required number of offspring from asexual reproduction.
for (int i = 0; i < inst._offspringAsexualCount; i++)
{
int genomeIdx = DiscreteDistribution.Sample(_rng, dist);
TGenome offspring = genomeList[genomeIdx].CreateOffspring(_currentGeneration);
offspringList.Add(offspring);
}
_stats._asexualOffspringCount += (ulong)inst._offspringAsexualCount;
// --- Produce the required number of offspring from sexual reproduction.
// Cross-specie mating.
// If nonZeroSpecieCount is exactly 1 then we skip inter-species mating. One is a special case because
// for 0 the species all get an even chance of selection, and for >1 we can just select species normally.
int crossSpecieMatings = nonZeroSpecieCount == 1 ? 0 :
(int)NumericsUtils.ProbabilisticRound(_eaParams.InterspeciesMatingProportion
* inst._offspringSexualCount, _rng);
_stats._sexualOffspringCount += (ulong)(inst._offspringSexualCount - crossSpecieMatings);
_stats._interspeciesOffspringCount += (ulong)crossSpecieMatings;
// An index that keeps track of how many offspring have been produced in total.
int matingsCount = 0;
for (; matingsCount < crossSpecieMatings; matingsCount++)
{
TGenome offspring = CreateOffspring_CrossSpecieMating(dist, distArr, rwlSpecies, specieIdx, genomeList);
offspringList.Add(offspring);
}
// For the remainder we use normal intra-specie mating.
// Test for special case - we only have one genome to select from in the current specie.
if (1 == inst._selectionSizeInt)
{
// Fall-back to asexual reproduction.
for (; matingsCount < inst._offspringSexualCount; matingsCount++)
{
int genomeIdx = DiscreteDistribution.Sample(_rng, dist);
TGenome offspring = genomeList[genomeIdx].CreateOffspring(_currentGeneration);
offspringList.Add(offspring);
}
}
else
{
// Remainder of matings are normal within-specie.
for (; matingsCount < inst._offspringSexualCount; matingsCount++)
{
// Select parent 1.
int parent1Idx = DiscreteDistribution.Sample(_rng, dist);
TGenome parent1 = genomeList[parent1Idx];
// Remove selected parent from set of possible outcomes.
DiscreteDistribution distTmp = dist.RemoveOutcome(parent1Idx);
// Test for existence of at least one more parent to select.
if (0 != distTmp.Probabilities.Length)
{ // Get the two parents to mate.
int parent2Idx = DiscreteDistribution.Sample(_rng, distTmp);
TGenome parent2 = genomeList[parent2Idx];
TGenome offspring = parent1.CreateOffspring(parent2, _currentGeneration);
offspringList.Add(offspring);
}
else
{ // No other parent has a non-zero selection probability (they all have zero fitness).
// Fall back to asexual reproduction of the single genome with a non-zero fitness.
TGenome offspring = parent1.CreateOffspring(_currentGeneration);
offspringList.Add(offspring);
}
}
}
}
_stats._totalOffspringCount += (ulong)offspringCount;
return(offspringList);
}
