private NeatGenome <T> CreateGenomeInner(NeatGenome <T> parent1, NeatGenome <T> parent2)
{
// Randomly select one parent as being the primary parent.
if (_rng.NextBool())
{
VariableUtils.Swap(ref parent1, ref parent2);
}
// Enumerate over the connection genes in both parents.
foreach (var geneIndexPair in EnumerateParentGenes(parent1.ConnectionGenes, parent2.ConnectionGenes))
{
// Create a connection gene based on the current position in both parents.
ConnectionGene <T>?connGene = CreateConnectionGene(
parent1.ConnectionGenes, parent2.ConnectionGenes,
geneIndexPair.Item1, geneIndexPair.Item2,
out bool isSecondaryGene);
if (connGene.HasValue)
{
// Attempt to add the gene to the child genome we are building.
_builder.TryAddGene(connGene.Value, isSecondaryGene);
}
}
// Convert the genes to the structure required by NeatGenome.
var connGenes = _builder.ToConnectionGenes();
// Create and return a new genome.
return(_genomeBuilder.Create(
_genomeIdSeq.Next(),
_generationSeq.Peek,
connGenes));
}
/// <summary>
/// Initialise an array with 'naturally' random integers.
/// The array will contain sub-spans of sorted integers, in both ascending and descending order.
/// </summary>
/// <param name="arr">The array to initialise.</param>
/// <param name="rng">Random number generator.</param>
public static void InitNatural(int[] arr, IRandomSource rng)
{
// Init with an incrementing sequence.
for (int i = 0; i < arr.Length; i++)
{
arr[i] = i;
}
// Reverse multiple random sub-ranges.
int reverseCount = (int)(Math.Sqrt(arr.Length) * 2.0);
int len = arr.Length;
for (int i = 0; i < reverseCount; i++)
{
int idx = rng.Next(arr.Length);
int idx2 = rng.Next(arr.Length);
if (idx > idx2)
{
VariableUtils.Swap(ref idx, ref idx2);
}
if (i % 2 == 0)
{
Array.Reverse(arr, 0, idx + 1);
Array.Reverse(arr, idx2, len - idx2);
}
else
{
Array.Reverse(arr, idx, idx2 - idx);
}
}
}
/// <summary>
/// Initialise a span with 'naturally' ordered random integers.
/// The initialised span will contain sub-spans of sorted integers, in both ascending and descending order.
/// </summary>
/// <param name="keys">The span to initialise.</param>
/// <param name="rng">Random number generator.</param>
public static void InitNatural(Span <int> keys, IRandomSource rng)
{
// Init with an incrementing sequence.
for (int i = 0; i < keys.Length; i++)
{
keys[i] = i;
}
// Reverse multiple random sub-ranges.
int reverseCount = (int)(Math.Sqrt(keys.Length) * 2.0);
int len = keys.Length;
for (int i = 0; i < reverseCount; i++)
{
int idx = rng.Next(keys.Length);
int idx2 = rng.Next(keys.Length);
if (idx > idx2)
{
VariableUtils.Swap(ref idx, ref idx2);
}
if (rng.NextBool())
{
keys[0..idx].Reverse();
public void IterationSetup_NaturallyOrderedKeys()
{
// Init with an incrementing sequence.
for (int i = 0; i < _keys.Length; i++)
{
_keys[i] = i;
}
// Reverse multiple random sub-ranges.
int reverseCount = (int)(Math.Sqrt(_keys.Length) * 2.0);
int len = _keys.Length;
for (int i = 0; i < reverseCount; i++)
{
int idx = _rng.Next(len);
int idx2 = _rng.Next(len);
if (idx > idx2)
{
VariableUtils.Swap(ref idx, ref idx2);
}
if (_rng.NextBool())
{
Array.Reverse(_keys, 0, idx + 1);
Array.Reverse(_keys, idx2, len - idx2);
}
else
{
Array.Reverse(_keys, idx, idx2 - idx);
}
}
// Init value arrays (just copy key value into these).
for (int i = 0; i < _keys.Length; i++)
{
_values[i] = _keys[i];
_values2[i] = _keys[i];
}
}
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)
{
// Calc the number of offspring to create via inter-species sexual reproduction.
int offspringCountSexualInter;
if (interspeciesMatingProportion == 0.0)
{
offspringCountSexualInter = 0;
}
else
{
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 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);
}
// 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);
}
}