private void Evaluate_Caching(IList <TGenome> genomeList)
{
// Decode and evaluate each genome in turn.
foreach (TGenome genome in genomeList)
{
TPhenome phenome = (TPhenome)genome.CachedPhenome;
if (null == phenome)
{ // Decode the phenome and store a ref against the genome.
phenome = _genomeDecoder.Decode(genome);
genome.CachedPhenome = phenome;
}
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AlternativeFitness = 0.0;
}
else
{
FitnessInfo fitnessInfo = _phenomeEvaluator.Evaluate(phenome);
genome.EvaluationInfo.SetFitness(fitnessInfo._fitness);
genome.EvaluationInfo.AlternativeFitness = fitnessInfo._alternativeFitness;
}
}
}
private IEnumerator Evaluate_Caching(IList <TGenome> genomeList)
{
// Decode and evaluate each genome in turn.
foreach (TGenome genome in genomeList)
{
TPhenome phenome = (TPhenome)genome.CachedPhenome;
if (null == phenome)
{ // Decode the phenome and store a ref against the genome.
phenome = _genomeDecoder.Decode(genome);
genome.CachedPhenome = phenome;
}
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
_phenomeEvaluator.Evaluate(phenome);
FitnessInfo fitnessInfo = _phenomeEvaluator.GetLastFitness(phenome);
genome.EvaluationInfo.SetFitness(fitnessInfo._fitness);
genome.EvaluationInfo.AuxFitnessArr = fitnessInfo._auxFitnessArr;
}
}
return(null);
}
/// <summary>
/// Main genome evaluation loop with phenome caching (decode only if no cached phenome is present
/// from a previous decode).
/// </summary>
private void Evaluate_Caching(IList <TGenome> genomeList)
{
_phenomeEvaluator.NewGeneration();
Parallel.ForEach(genomeList, _parallelOptions, delegate(TGenome genome)
{
TPhenome phenome = (TPhenome)genome.CachedPhenome;
if (null == phenome)
{ // Decode the phenome and store a ref against the genome.
phenome = _genomeDecoder.Decode(genome);
genome.CachedPhenome = phenome;
}
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
FitnessInfo fitnessInfo = _phenomeEvaluator.Evaluate(phenome);
if (SharedParams.SharedParams.USEFITNESSBANK)
{
genome.EvaluationInfo.SetFitness(genome.EvaluationInfo.Fitness * (1 - SharedParams.SharedParams.FITNESSBANKDECAYRATE) + fitnessInfo._fitness);
}
else
{
genome.EvaluationInfo.SetFitness(fitnessInfo._fitness);
}
genome.EvaluationInfo.AuxFitnessArr = fitnessInfo._auxFitnessArr;
}
});
}
private void EvaluateOne(TGenome genome, TPhenome phenome, string userName)
{
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
FitnessInfo fitnessInfo = _phenomeEvaluator.Evaluate(phenome, genome.CandidateName, userName);
// We don't want to update fitness in this way in the website-based project.
// See evolution algorithm.
//genome.EvaluationInfo.SetFitness(fitnessInfo._fitness);
//genome.EvaluationInfo.AuxFitnessArr = fitnessInfo._auxFitnessArr;
}
}
/// <summary>
/// Main genome evaluation loop with no phenome caching (decode on each loop).
/// </summary>
private void Evaluate_NonCaching(IList <TGenome> genomeList)
{
Parallel.ForEach(genomeList, _parallelOptions, delegate(TGenome genome)
{
TPhenome phenome = _genomeDecoder.Decode(genome);
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
FitnessInfo fitnessInfo = _phenomeEvaluator.Evaluate(phenome);
genome.EvaluationInfo.SetFitness(fitnessInfo._fitness);
genome.EvaluationInfo.AuxFitnessArr = fitnessInfo._auxFitnessArr;
}
});
}
private void EvaluateOne(TGenome genome, TPhenome phenome, ParallelEvaluationParameters parameters)
{
if (null == phenome)
{ // Non-viable genome.
System.Diagnostics.Debug.WriteLine("Non-viable phenome found");
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
System.Diagnostics.Debug.WriteLine("Evaluate one calls pseudoevaluator.");
FitnessInfo fitnessInfo = _phenomeEvaluator.Evaluate(phenome, parameters);
// We don't want to update fitness in this way in the website-based project.
// See evolution algorithm.
//genome.EvaluationInfo.SetFitness(fitnessInfo._fitness);
//genome.EvaluationInfo.AuxFitnessArr = fitnessInfo._auxFitnessArr;
}
}
private void Evaluate_NonCaching(IList <TGenome> genomeList)
{
// Decode and evaluate each genome in turn.
foreach (TGenome genome in genomeList)
{
TPhenome phenome = _genomeDecoder.Decode(genome);
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AuxFitnessArr = null;
}
else
{
FitnessInfo fitnessInfo = _phenomeEvaluator.Evaluate(phenome, genome);
genome.EvaluationInfo.SetFitness(fitnessInfo._fitness);
genome.EvaluationInfo.AuxFitnessArr = fitnessInfo._auxFitnessArr;
}
}
}
/// <summary>
/// Main genome evaluation loop with phenome caching (decode only if no cached phenome is present
/// from a previous decode).
/// </summary>
private void Evaluate_Caching(IList <TGenome> genomeList)
{
Parallel.ForEach(genomeList, _parallelOptions, delegate(TGenome genome)
{
TPhenome phenome = (TPhenome)genome.CachedPhenome;
if (null == phenome)
{ // Decode the phenome and store a ref against the genome.
phenome = _genomeDecoder.Decode(genome);
genome.CachedPhenome = phenome;
}
if (null == phenome)
{ // Non-viable genome.
genome.EvaluationInfo.SetFitness(0.0);
genome.EvaluationInfo.AlternativeFitness = 0.0;
}
else
{
FitnessInfo fitnessInfo = _phenomeEvaluator.Evaluate(phenome);
genome.EvaluationInfo.SetFitness(fitnessInfo._fitness);
genome.EvaluationInfo.AlternativeFitness = fitnessInfo._alternativeFitness;
}
});
}
//readonly ParallelOptions _parallelOptions;
/// <summary>
/// Main genome evaluation loop with no phenome caching (decode
/// on each evaluation). Individuals are competed pairwise against
/// every other in the population.
/// Evaluations are summed to get the final genome fitness.
/// </summary>
public void Evaluate(IList <TGenome> genomeList)
{
//Create a temporary list of fitness values
FitnessInfo[] results = new FitnessInfo[genomeList.Count];
for (int i = 0; i < results.Length; i++)
{
results[i] = FitnessInfo.Zero;
}
// Exhaustively compete individuals against each other.
for (int i = 0; i < genomeList.Count; i++)
{
for (int j = 0; j < genomeList.Count; j++)
{
// Don't bother evaluating inviduals against themselves.
if (i == j)
{
continue;
}
// Decode the first genome.
TPhenome phenome1 = _genomeDecoder.Decode(genomeList[i]);
// Check that the first genome is valid.
if (phenome1 == null)
{
continue;
}
// Decode the second genome.
TPhenome phenome2 = _genomeDecoder.Decode(genomeList[j]);
// Check that the second genome is valid.
if (phenome2 == null)
{
continue;
}
// Compete the two individuals against each other and get
// the results.
FitnessInfo fitness1, fitness2;
_phenomeEvaluator.Evaluate(phenome1, phenome2,
out fitness1, out fitness2);
// Add the results to each genome's overall fitness.
// Note that we need to use a lock here because
// the += operation is not atomic.
lock (results)
{
results[i]._fitness += fitness1._fitness;
//results[i]._alternativeFitness +=
// fitness1._alternativeFitness;
results[j]._fitness += fitness2._fitness;
//results[j]._alternativeFitness +=
// fitness2._alternativeFitness;
}
}
}
// Update every genome in the population with its new fitness score.
for (int i = 0; i < results.Length; i++)
{
genomeList[i].EvaluationInfo.SetFitness(results[i]._fitness);
//genomeList[i].EvaluationInfo.AlternativeFitness =
// results[i]._alternativeFitness;
}
}
