public GeneticAlgorithm CreateGpArtificialAntSample() {
GeneticAlgorithm ga = new GeneticAlgorithm();
#region Problem Configuration
Problem antProblem = new Problem();
antProblem.BestKnownQuality = 89;
antProblem.Encoding.TreeDepth = 10;
antProblem.Encoding.TreeLength = 100;
antProblem.Encoding.FunctionDefinitions = 3;
antProblem.Encoding.FunctionArguments = 3;
antProblem.MaxTimeSteps.Value = 600;
#endregion
#region Algorithm Configuration
ga.Name = "Genetic Programming - Artificial Ant";
ga.Description = "A standard genetic programming algorithm to solve the artificial ant problem (Santa-Fe trail)";
ga.Problem = antProblem;
SamplesUtils.ConfigureGeneticAlgorithmParameters<TournamentSelector, SubtreeCrossover, MultiSymbolicExpressionTreeArchitectureManipulator>(
ga, 1000, 1, 50, 0.15, 5);
var mutator = (MultiSymbolicExpressionTreeArchitectureManipulator)ga.Mutator;
mutator.Operators.SetItemCheckedState(mutator.Operators
.OfType<FullTreeShaker>()
.Single(), false);
mutator.Operators.SetItemCheckedState(mutator.Operators
.OfType<OnePointShaker>()
.Single(), false);
mutator.Operators.SetItemCheckedState(mutator.Operators
.OfType<ArgumentDeleter>()
.Single(), false);
mutator.Operators.SetItemCheckedState(mutator.Operators
.OfType<SubroutineDeleter>()
.Single(), false);
#endregion
return ga;
}
public GEArtificialAntProblem()
: base()
{
wrappedAntProblem = new HeuristicLab.Problems.GeneticProgramming.ArtificialAnt.Problem();
Parameters.Add(new ValueParameter <BoolMatrix>("World", "The world for the artificial ant with scattered food items.", wrappedAntProblem.World));
Parameters.Add(new FixedValueParameter <IntValue>("MaximumTimeSteps", "The number of time steps the artificial ant has available to collect all food items.", new IntValue(600)));
Parameters.Add(new ValueParameter <IGenotypeToPhenotypeMapper>("GenotypeToPhenotypeMapper", "Maps the genotype (an integer vector) to the phenotype (a symbolic expression tree).", new DepthFirstMapper()));
Encoding = new IntegerVectorEncoding(30)
{
Bounds = new IntMatrix(new int[, ] {
{ 0, 100 }
})
};
BestKnownQuality = wrappedAntProblem.BestKnownQuality;
}
private GEArtificialAntProblem(GEArtificialAntProblem original, Cloner cloner)
: base(original, cloner)
{
this.wrappedAntProblem = cloner.Clone(original.wrappedAntProblem);
}
// cloning
private Problem(Problem original, Cloner cloner) : base(original, cloner)
{
}
