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));
}
private static ConnectionGene <T>?CreateConnectionGene(
ConnectionGenes <T> connGenes1,
ConnectionGenes <T> connGenes2,
int idx1, int idx2,
bool includeSecondaryParentGene,
IRandomSource rng)
{
// Select gene at random if it is present on both parents.
if (idx1 != -1 && idx2 != -1)
{
if (rng.NextBool())
{
return(CreateConnectionGene(connGenes1, idx1));
}
else
{
return(CreateConnectionGene(connGenes2, idx2));
}
}
// Use the primary parent's gene if it has one.
if (idx1 != -1)
{
return(CreateConnectionGene(connGenes1, idx1));
}
// Otherwise use the secondary parent's gene if the 'includeSecondaryParentGene' flag is set.
if (includeSecondaryParentGene)
{
return(CreateConnectionGene(connGenes2, idx2));
}
return(null);
}
/// <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();
private ConnectionGene <T>?CreateConnectionGene(
ConnectionGenes <T> connGenes1,
ConnectionGenes <T> connGenes2,
int idx1, int idx2,
IRandomSource rng)
{
// Select gene at random if it is present on both parents.
if (-1 != idx1 && -1 != idx2)
{
if (rng.NextBool())
{
return(CreateConnectionGene(connGenes1, idx1));
}
else
{
return(CreateConnectionGene(connGenes2, idx2));
}
}
// Use the primary parent's gene if it has one.
if (-1 != idx1)
{
return(CreateConnectionGene(connGenes1, idx1));
}
// Otherwise use the secondary parent's gene stochastically.
if (DiscreteDistribution.SampleBernoulli(rng, _secondaryParentGeneProbability))
{
return(CreateConnectionGene(connGenes2, idx2));
}
return(null);
}
/// <summary>
/// Create a new child genome from a given parent genome.
/// </summary>
/// <param name="parent">The parent genome.</param>
/// <returns>A new child genome.</returns>
public NeatGenome <T> CreateChildGenome(NeatGenome <T> parent)
{
Debug.Assert(_metaNeatGenome == parent.MetaNeatGenome, "Parent genome has unexpected MetaNeatGenome.");
// Attempt to find a new connection that we can add to the genome.
DirectedConnection directedConn;
if (!TryGetConnection(parent, out directedConn, out int insertIdx))
{ // Failed to find a new connection.
return(null);
}
// Determine the connection weight.
// 50% of the time use weights very close to zero.
// Note. this recreates the strategy used in SharpNEAT 2.x.
// ENHANCEMENT: Reconsider the distribution of new weights and if there are better approaches (distributions) we could use.
T weight = _rng.NextBool() ? _weightDistB.Sample() : _weightDistA.Sample();
// Create a new connection gene array that consists of the parent connection genes plus the new gene
// inserted at the correct (sorted) position.
var parentConnArr = parent.ConnectionGenes._connArr;
var parentWeightArr = parent.ConnectionGenes._weightArr;
int parentLen = parentConnArr.Length;
// Create the child genome's ConnectionGenes object.
int childLen = parentLen + 1;
var connGenes = new ConnectionGenes <T>(childLen);
var connArr = connGenes._connArr;
var weightArr = connGenes._weightArr;
// Copy genes up to insertIdx.
Array.Copy(parentConnArr, connArr, insertIdx);
Array.Copy(parentWeightArr, weightArr, insertIdx);
// Copy the new genome into its insertion point.
connArr[insertIdx] = new DirectedConnection(
directedConn.SourceId,
directedConn.TargetId);
weightArr[insertIdx] = weight;
// Copy remaining genes (if any).
Array.Copy(parentConnArr, insertIdx, connArr, insertIdx + 1, parentLen - insertIdx);
Array.Copy(parentWeightArr, insertIdx, weightArr, insertIdx + 1, parentLen - insertIdx);
// Create and return a new genome.
// Notes.
// The set of hidden node IDs remains unchanged from the parent, therefore we are able to re-use parent.HiddenNodeIdArray.
// However, the presence of a new connection invalidates parent.NodeIndexByIdMap for use in the new genome, because the allocated
// node indexes are dependent on node depth in the acyclic graph, which in turn can be modified by the presence of a new connection.
return(_genomeBuilder.Create(
_genomeIdSeq.Next(),
_generationSeq.Peek,
connGenes,
parent.HiddenNodeIdArray));
}
/// <summary>
/// Take a sample from the uniform distribution with interval (-1, 1).
/// </summary>
/// <param name="rng">Random source.</param>
/// <returns>A random sample.</returns>
public static float SampleSigned(IRandomSource rng)
{
float sample = rng.NextFloat();
if (rng.NextBool())
{
sample *= -1.0f;
}
return(sample);
}
/// <summary>
/// Take a sample from the uniform distribution with interval (-1, 1).
/// </summary>
/// <param name="rng">Random source.</param>
/// <returns>A random sample.</returns>
public static double SampleSigned(IRandomSource rng)
{
double sample = rng.NextDouble();
if (rng.NextBool())
{
sample *= -1.0f;
}
return(sample);
}
/// <summary>
/// Take a sample from the uniform distribution with interval (-max, max).
/// </summary>
/// <param name="rng">Random source.</param>
/// <param name="max">Maximum absolute value (exclusive).</param>
/// <returns>A random sample.</returns>
public static float SampleSigned(IRandomSource rng, float max)
{
Debug.Assert(max >= 0.0);
float sample = rng.NextFloat() * max;
if (rng.NextBool())
{
sample *= -1.0f;
}
return(sample);
}
/// <summary>
/// Take a sample from the uniform distribution with interval (-max, max).
/// </summary>
/// <param name="rng">Random source.</param>
/// <param name="max">Maximum absolute value (exclusive).</param>
/// <returns>A random sample.</returns>
public static double SampleSigned(IRandomSource rng, double max)
{
Debug.Assert(max >= 0.0);
double sample = rng.NextDouble() * max;
if (rng.NextBool())
{
sample *= -1.0;
}
return(sample);
}
/// <summary>
/// Create a new child genome from a given parent genome.
/// </summary>
/// <param name="parent">The parent genome.</param>
/// <param name="rng">Random source.</param>
/// <returns>A new child genome.</returns>
public NeatGenome <T>?CreateChildGenome(NeatGenome <T> parent, IRandomSource rng)
{
// Attempt to find a new connection that we can add to the genome.
if (!TryGetConnection(parent, rng, out DirectedConnection directedConn, out int insertIdx))
{
// Failed to find a new connection.
return(null);
}
// Determine the connection weight.
// 50% of the time use weights very close to zero.
// Note. this recreates the strategy used in SharpNEAT 2.x.
// ENHANCEMENT: Reconsider the distribution of new weights and if there are better approaches (distributions) we could use.
T weight = rng.NextBool() ? _weightSamplerB.Sample(rng) : _weightSamplerA.Sample(rng);
// Create a new connection gene array that consists of the parent connection genes plus the new gene
// inserted at the correct (sorted) position.
var parentConnArr = parent.ConnectionGenes._connArr;
var parentWeightArr = parent.ConnectionGenes._weightArr;
int parentLen = parentConnArr.Length;
// Create the child genome's ConnectionGenes object.
int childLen = parentLen + 1;
var connGenes = new ConnectionGenes <T>(childLen);
var connArr = connGenes._connArr;
var weightArr = connGenes._weightArr;
// Copy genes up to insertIdx.
Array.Copy(parentConnArr, connArr, insertIdx);
Array.Copy(parentWeightArr, weightArr, insertIdx);
// Copy the new genome into its insertion point.
connArr[insertIdx] = new DirectedConnection(
directedConn.SourceId,
directedConn.TargetId);
weightArr[insertIdx] = weight;
// Copy remaining genes (if any).
Array.Copy(parentConnArr, insertIdx, connArr, insertIdx + 1, parentLen - insertIdx);
Array.Copy(parentWeightArr, insertIdx, weightArr, insertIdx + 1, parentLen - insertIdx);
// Create and return a new genome.
// Note. The set of hidden node IDs remains unchanged from the parent, therefore we are able to re-use
// both parent.HiddenNodeIdArray and NodeIndexByIdMap.
return(_genomeBuilder.Create(
_genomeIdSeq.Next(),
_generationSeq.Peek,
connGenes,
parent.HiddenNodeIdArray,
parent.NodeIndexByIdMap));
}
/// <summary>
/// Fill an array with samples from the uniform distribution with interval (-max, max).
/// </summary>
/// <param name="rng">Random source.</param>
/// <param name="max">Maximum absolute value (exclusive).</param>
/// <param name="buf">The array to fill with samples.</param>
public static void SampleSigned(IRandomSource rng, float max, float[] buf)
{
Debug.Assert(max >= 0.0);
for (int i = 0; i < buf.Length; i++)
{
float sample = rng.NextFloat() * max;
if (rng.NextBool())
{
sample *= -1.0f;
}
buf[i] = sample;
}
}
/// <summary>
/// Fill an array with samples from the uniform distribution with interval (-max, max).
/// </summary>
/// <param name="rng">Random source.</param>
/// <param name="max">Maximum absolute value (exclusive).</param>
/// <param name="buf">The array to fill with samples.</param>
public static void SampleSigned(IRandomSource rng, double max, double[] buf)
{
Debug.Assert(max >= 0.0);
for (int i = 0; i < buf.Length; i++)
{
double sample = rng.NextDouble() * max;
if (rng.NextBool())
{
sample *= -1.0;
}
buf[i] = sample;
}
}
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 IntPoint[] GenerateRandomTestCase(int largeBoxRelativePos)
{
// Randomly select a position for the small box (the box is a single pixel in size).
IntPoint smallBoxPos = new IntPoint(_rng.Next(TestFieldResolution), _rng.Next(TestFieldResolution));
// Large box center is 5 pixels to the right, down or diagonally from the small box.
IntPoint largeBoxPos = smallBoxPos;
switch (largeBoxRelativePos)
{
case 0: // Right
largeBoxPos._x += 5;
break;
case 1: // Down
largeBoxPos._y += 5;
break;
case 2: // Diagonal
// Two alternate position get us to exactly 5 pixels distant from the small box.
if (_rng.NextBool())
{
largeBoxPos._x += 3;
largeBoxPos._y += 4;
}
else
{
largeBoxPos._x += 4;
largeBoxPos._y += 3;
}
break;
}
// Handle cases where the large box is outside the visual field or overlapping the edge.
if (largeBoxPos._x > CoordBoundIdx)
{ // Wrap around.
largeBoxPos._x -= TestFieldResolution;
if (0 == largeBoxPos._x)
{ // Move box fully into the visual field.
largeBoxPos._x++;
}
}
else if (CoordBoundIdx == largeBoxPos._x)
{ // Move box fully into the visual field.
largeBoxPos._x--;
}
else if (0 == largeBoxPos._x)
{ // Move box fully into the visual field.
largeBoxPos._x++;
}
if (largeBoxPos._y > CoordBoundIdx)
{ // Wrap around.
largeBoxPos._y -= TestFieldResolution;
if (0 == largeBoxPos._y)
{ // Move box fully into the visual field.
largeBoxPos._y++;
}
}
else if (CoordBoundIdx == largeBoxPos._y)
{ // Move box fully into the visual field.
largeBoxPos._y--;
}
else if (0 == largeBoxPos._y)
{ // Move box fully into the visual field.
largeBoxPos._y++;
}
return(new IntPoint[] { smallBoxPos, largeBoxPos });
}