private PrgPopulation Create()
{
EncogProgramContext context = new EncogProgramContext();
context.DefineVariable("x");
StandardExtensions.CreateAll(context);
PrgPopulation pop = new PrgPopulation(context, 10);
EncogProgram prg1 = new EncogProgram(context);
EncogProgram prg2 = new EncogProgram(context);
prg1.CompileExpression("x+1");
prg2.CompileExpression("(x+5)/2");
ISpecies defaultSpecies = pop.CreateSpecies();
defaultSpecies.Add(prg1);
defaultSpecies.Add(prg2);
return(pop);
}
/// <summary>
/// Add a population member from one of the threads.
/// </summary>
/// <param name="population">The population to add to.</param>
/// <param name="prg">The program to add.</param>
public void AddPopulationMember(IPopulation population,
EncogProgram prg)
{
lock (this)
{
ISpecies defaultSpecies = population.Species[0];
prg.Species = defaultSpecies;
defaultSpecies.Add(prg);
_contents.Add(prg.DumpAsCommonExpression());
}
}
/// <summary>
/// Construct a method genetic algorithm.
/// </summary>
/// <param name="phenotypeFactory">The phenotype factory.</param>
/// <param name="calculateScore">The score calculation object.</param>
/// <param name="populationSize">The population size.</param>
public MLMethodGeneticAlgorithm(MLMethodGenomeFactory.CreateMethod phenotypeFactory,
ICalculateScore calculateScore, int populationSize)
: base(TrainingImplementationType.Iterative)
{
// create the population
IPopulation population = new BasicPopulation(populationSize, null);
population.GenomeFactory = new MLMethodGenomeFactory(phenotypeFactory,
population);
ISpecies defaultSpecies = population.CreateSpecies();
for (int i = 0; i < population.PopulationSize; i++)
{
IMLEncodable chromosomeNetwork = (IMLEncodable)phenotypeFactory();
MLMethodGenome genome = new MLMethodGenome(chromosomeNetwork);
defaultSpecies.Add(genome);
}
defaultSpecies.Leader = defaultSpecies.Members[0];
// create the trainer
this.genetic = new MLMethodGeneticAlgorithmHelper(population,
calculateScore);
this.genetic.CODEC = new MLEncodableCODEC();
IGenomeComparer comp = null;
if (calculateScore.ShouldMinimize)
{
comp = new MinimizeScoreComp();
}
else
{
comp = new MaximizeScoreComp();
}
this.genetic.BestComparer = comp;
this.genetic.SelectionComparer = comp;
// create the operators
int s = Math
.Max(defaultSpecies.Members[0].Size / 5, 1);
Genetic.Population = population;
this.genetic.AddOperation(0.9, new Splice(s));
this.genetic.AddOperation(0.1, new MutatePerturb(1.0));
}
/// <summary>
/// Add a genome.
/// </summary>
/// <param name="species">The species to add to.</param>
/// <param name="genome">The genome to add.</param>
public void AddSpeciesMember(ISpecies species, IGenome genome)
{
if (_owner.ValidationMode)
{
if (species.Members.Contains(genome))
{
throw new GeneticError("Species already contains genome: "
+ genome);
}
}
if (_owner.SelectionComparer.Compare(genome,
species.Leader) < 0)
{
species.BestScore = genome.AdjustedScore;
species.GensNoImprovement = 0;
species.Leader = genome;
}
species.Add(genome);
}
/// <summary>
/// Add a genome.
/// </summary>
/// <param name="species">The species to add to.</param>
/// <param name="genome">The genome to add.</param>
public void AddSpeciesMember(ISpecies species, IGenome genome)
{
if (_owner.ValidationMode)
{
if (species.Members.Contains(genome))
{
throw new GeneticError("Species already contains genome: "
+ genome);
}
}
if (_owner.SelectionComparer.Compare(genome,
species.Leader) < 0)
{
species.BestScore = genome.AdjustedScore;
species.GensNoImprovement = 0;
species.Leader = genome;
}
species.Add(genome);
}
