public OffspringSelectionGeneticAlgorithm CreateGeSymbolicRegressionSample()
{
var ga = new OffspringSelectionGeneticAlgorithm();
#region Problem Configuration
var problem = new HeuristicLab.Problems.GrammaticalEvolution.GESymbolicRegressionSingleObjectiveProblem();
#endregion
#region Algorithm Configuration
ga.Name = "Grammatical Evolution - Symbolic Regression (Poly-10)";
ga.Description = "Grammatical evolution algorithm for solving a symbolic regression problem problem";
ga.Problem = problem;
problem.Load(new PolyTen().GenerateRegressionData());
// must occur after loading problem data because the grammar creates symbols for random constants once the data is loaded
var consts = problem.SymbolicExpressionTreeGrammar.AllowedSymbols.OfType <Constant>().ToList();
foreach (var c in consts)
{
problem.SymbolicExpressionTreeGrammar.RemoveSymbol(c);
}
SamplesUtils.ConfigureOsGeneticAlgorithmParameters <GenderSpecificSelector, Encodings.IntegerVectorEncoding.SinglePointCrossover, Encodings.IntegerVectorEncoding.UniformOnePositionManipulator>(
ga, 1000, 1, 50, 0.05, 200);
#endregion
return(ga);
}
public static OffspringSelectionGeneticAlgorithm CreateGpTimeSeriesSample()
{
var problem = new SymbolicTimeSeriesPrognosisSingleObjectiveProblem();
problem.Name = "Symbolic time series prognosis problem (Mackey Glass t=17)";
problem.ProblemData.Name = "Mackey Glass t=17";
problem.MaximumSymbolicExpressionTreeLength.Value = 125;
problem.MaximumSymbolicExpressionTreeDepth.Value = 12;
problem.EvaluatorParameter.Value.HorizonParameter.Value.Value = 10;
foreach (var symbol in problem.SymbolicExpressionTreeGrammar.Symbols)
{
if (symbol is Exponential || symbol is Logarithm)
{
symbol.Enabled = false;
}
else if (symbol is AutoregressiveTargetVariable)
{
symbol.Enabled = true;
var autoRegressiveSymbol = symbol as AutoregressiveTargetVariable;
autoRegressiveSymbol.MinLag = -30;
autoRegressiveSymbol.MaxLag = -1;
}
}
var osga = new OffspringSelectionGeneticAlgorithm();
osga.Name = "Genetic Programming - Time Series Prediction (Mackey-Glass-17)";
osga.Description = "A genetic programming algorithm for creating a time-series model for the Mackey-Glass-17 time series.";
osga.Problem = problem;
SamplesUtils.ConfigureOsGeneticAlgorithmParameters <GenderSpecificSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>
(osga, popSize: 100, elites: 1, maxGens: 25, mutationRate: 0.15);
osga.MaximumSelectionPressure.Value = 100;
return(osga);
}
public static void ConfigureOsGeneticAlgorithmParameters <S, C, M>(OffspringSelectionGeneticAlgorithm ga, int popSize, int elites, int maxGens, double mutationRate = 0.05, double maxSelPres = 100, int tournGroupSize = 0)
where S : ISelector
where C : ICrossover
where M : IManipulator
{
ga.Elites.Value = elites;
ga.MaximumGenerations.Value = maxGens;
ga.MutationProbability.Value = mutationRate;
ga.PopulationSize.Value = popSize;
ga.MaximumSelectionPressure.Value = maxSelPres;
ga.Seed.Value = 0;
ga.SetSeedRandomly.Value = true;
ga.ComparisonFactorLowerBound.Value = 1;
ga.ComparisonFactorUpperBound.Value = 1;
ga.Selector = ga.SelectorParameter.ValidValues
.OfType <S>()
.First();
ga.Crossover = ga.CrossoverParameter.ValidValues
.OfType <C>()
.First();
ga.Mutator = ga.MutatorParameter.ValidValues
.OfType <M>()
.First();
var tSelector = ga.Selector as TournamentSelector;
if (tSelector != null)
{
tSelector.GroupSizeParameter.Value.Value = tournGroupSize;
}
ga.Engine = new ParallelEngine.ParallelEngine();
}
public OffspringSelectionGeneticAlgorithm CreateGeArtificialAntSample()
{
OffspringSelectionGeneticAlgorithm ga = new OffspringSelectionGeneticAlgorithm();
#region Problem Configuration
var problem = new HeuristicLab.Problems.GrammaticalEvolution.GEArtificialAntProblem();
#endregion
#region Algorithm Configuration
ga.Name = "Grammatical Evolution - Artificial Ant (SantaFe)";
ga.Description = "Grammatical evolution algorithm for solving a artificial ant problem";
ga.Problem = problem;
SamplesUtils.ConfigureOsGeneticAlgorithmParameters <GenderSpecificSelector, Encodings.IntegerVectorEncoding.SinglePointCrossover, Encodings.IntegerVectorEncoding.UniformOnePositionManipulator>(
ga, 200, 1, 50, 0.05, 200);
#endregion
return(ga);
}
public static OffspringSelectionGeneticAlgorithm CreateGpMultiplexerSample()
{
var problem = new HeuristicLab.Problems.GeneticProgramming.Boolean.MultiplexerProblem();
problem.Name = "11-Multiplexer Problem";
problem.Encoding.TreeLength = 50;
problem.Encoding.TreeDepth = 50;
var osga = new OffspringSelectionGeneticAlgorithm();
osga.Name = "Genetic Programming - Multiplexer 11 Problem";
osga.Description = "A genetic programming algorithm that solves the 11-bit multiplexer problem.";
osga.Problem = problem;
SamplesUtils.ConfigureOsGeneticAlgorithmParameters <GenderSpecificSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>
(osga, popSize: 100, elites: 1, maxGens: 50, mutationRate: 0.25);
osga.MaximumSelectionPressure.Value = 200;
return(osga);
}
private OffspringSelectionGeneticAlgorithm CreateGpSymbolicRegressionSample()
{
var osga = new OffspringSelectionGeneticAlgorithm();
#region Problem Configuration
var provider = new VariousInstanceProvider(seed);
var instance = provider.GetDataDescriptors().First(x => x.Name.StartsWith("Spatial co-evolution"));
var problemData = (RegressionProblemData)provider.LoadData(instance);
var problem = new SymbolicRegressionSingleObjectiveProblem();
problem.ProblemData = problemData;
problem.Load(problemData);
problem.BestKnownQuality.Value = 1.0;
#region configure grammar
var grammar = (TypeCoherentExpressionGrammar)problem.SymbolicExpressionTreeGrammar;
grammar.ConfigureAsDefaultRegressionGrammar();
//symbols square, power, squareroot, root, log, exp, sine, cosine, tangent, variable
var square = grammar.Symbols.OfType <Square>().Single();
var power = grammar.Symbols.OfType <Power>().Single();
var squareroot = grammar.Symbols.OfType <SquareRoot>().Single();
var root = grammar.Symbols.OfType <Root>().Single();
var log = grammar.Symbols.OfType <Logarithm>().Single();
var exp = grammar.Symbols.OfType <Exponential>().Single();
var sine = grammar.Symbols.OfType <Sine>().Single();
var cosine = grammar.Symbols.OfType <Cosine>().Single();
var tangent = grammar.Symbols.OfType <Tangent>().Single();
var variable = grammar.Symbols.OfType <Variable>().Single();
var powerSymbols = grammar.Symbols.Single(s => s.Name == "Power Functions");
powerSymbols.Enabled = true;
square.Enabled = true;
square.InitialFrequency = 1.0;
foreach (var allowed in grammar.GetAllowedChildSymbols(square))
{
grammar.RemoveAllowedChildSymbol(square, allowed);
}
foreach (var allowed in grammar.GetAllowedChildSymbols(square, 0))
{
grammar.RemoveAllowedChildSymbol(square, allowed, 0);
}
grammar.AddAllowedChildSymbol(square, variable);
power.Enabled = false;
squareroot.Enabled = false;
foreach (var allowed in grammar.GetAllowedChildSymbols(squareroot))
{
grammar.RemoveAllowedChildSymbol(squareroot, allowed);
}
foreach (var allowed in grammar.GetAllowedChildSymbols(squareroot, 0))
{
grammar.RemoveAllowedChildSymbol(squareroot, allowed, 0);
}
grammar.AddAllowedChildSymbol(squareroot, variable);
root.Enabled = false;
log.Enabled = true;
log.InitialFrequency = 1.0;
foreach (var allowed in grammar.GetAllowedChildSymbols(log))
{
grammar.RemoveAllowedChildSymbol(log, allowed);
}
foreach (var allowed in grammar.GetAllowedChildSymbols(log, 0))
{
grammar.RemoveAllowedChildSymbol(log, allowed, 0);
}
grammar.AddAllowedChildSymbol(log, variable);
exp.Enabled = true;
exp.InitialFrequency = 1.0;
foreach (var allowed in grammar.GetAllowedChildSymbols(exp))
{
grammar.RemoveAllowedChildSymbol(exp, allowed);
}
foreach (var allowed in grammar.GetAllowedChildSymbols(exp, 0))
{
grammar.RemoveAllowedChildSymbol(exp, allowed, 0);
}
grammar.AddAllowedChildSymbol(exp, variable);
sine.Enabled = false;
foreach (var allowed in grammar.GetAllowedChildSymbols(sine))
{
grammar.RemoveAllowedChildSymbol(sine, allowed);
}
foreach (var allowed in grammar.GetAllowedChildSymbols(sine, 0))
{
grammar.RemoveAllowedChildSymbol(sine, allowed, 0);
}
grammar.AddAllowedChildSymbol(sine, variable);
cosine.Enabled = false;
foreach (var allowed in grammar.GetAllowedChildSymbols(cosine))
{
grammar.RemoveAllowedChildSymbol(cosine, allowed);
}
foreach (var allowed in grammar.GetAllowedChildSymbols(cosine, 0))
{
grammar.RemoveAllowedChildSymbol(cosine, allowed, 0);
}
grammar.AddAllowedChildSymbol(cosine, variable);
tangent.Enabled = false;
foreach (var allowed in grammar.GetAllowedChildSymbols(tangent))
{
grammar.RemoveAllowedChildSymbol(tangent, allowed);
}
foreach (var allowed in grammar.GetAllowedChildSymbols(tangent, 0))
{
grammar.RemoveAllowedChildSymbol(tangent, allowed, 0);
}
grammar.AddAllowedChildSymbol(tangent, variable);
#endregion
problem.SymbolicExpressionTreeGrammar = grammar;
// configure remaining problem parameters
problem.MaximumSymbolicExpressionTreeLength.Value = 50;
problem.MaximumSymbolicExpressionTreeDepth.Value = 12;
problem.MaximumFunctionDefinitions.Value = 0;
problem.MaximumFunctionArguments.Value = 0;
var evaluator = new SymbolicRegressionConstantOptimizationEvaluator();
evaluator.ConstantOptimizationIterations.Value = 5;
problem.EvaluatorParameter.Value = evaluator;
problem.RelativeNumberOfEvaluatedSamplesParameter.Hidden = true;
problem.SolutionCreatorParameter.Hidden = true;
#endregion
#region Algorithm Configuration
osga.Problem = problem;
osga.Name = "Offspring Selection Genetic Programming - Symbolic Regression";
osga.Description = "Genetic programming with strict offspring selection for solving a benchmark regression problem.";
SamplesUtils.ConfigureOsGeneticAlgorithmParameters <GenderSpecificSelector, SubtreeCrossover, MultiSymbolicExpressionTreeManipulator>(osga, 100, 1, 25, 0.2, 50);
var mutator = (MultiSymbolicExpressionTreeManipulator)osga.Mutator;
mutator.Operators.OfType <FullTreeShaker>().Single().ShakingFactor = 0.1;
mutator.Operators.OfType <OnePointShaker>().Single().ShakingFactor = 1.0;
osga.Analyzer.Operators.SetItemCheckedState(
osga.Analyzer.Operators
.OfType <SymbolicRegressionSingleObjectiveOverfittingAnalyzer>()
.Single(), false);
osga.Analyzer.Operators.SetItemCheckedState(
osga.Analyzer.Operators
.OfType <SymbolicDataAnalysisAlleleFrequencyAnalyzer>()
.First(), false);
osga.ComparisonFactorModifierParameter.Hidden = true;
osga.ComparisonFactorLowerBoundParameter.Hidden = true;
osga.ComparisonFactorUpperBoundParameter.Hidden = true;
osga.OffspringSelectionBeforeMutationParameter.Hidden = true;
osga.SuccessRatioParameter.Hidden = true;
osga.SelectedParentsParameter.Hidden = true;
osga.ElitesParameter.Hidden = true;
#endregion
return(osga);
}
