#region License Information
/* HeuristicLab
* Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*
* Author: Sabine Winkler
*/
#endregion
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.ArtificialAnt;
using HeuristicLab.Problems.GrammaticalEvolution.Mappers;
namespace HeuristicLab.Problems.GrammaticalEvolution {
[Item("GEArtificialAntEvaluator", "Evaluates an artificial ant solution for grammatical evolution.")]
[StorableClass]
public class GEArtificialAntEvaluator : SingleSuccessorOperator,
ISingleObjectiveEvaluator, ISymbolicExpressionTreeGrammarBasedOperator {
#region Parameter Properties
public ILookupParameter QualityParameter {
get { return (ILookupParameter)Parameters["Quality"]; }
}
// genotype:
public ILookupParameter IntegerVectorParameter {
get { return (ILookupParameter)Parameters["IntegerVector"]; }
}
// phenotype:
public ILookupParameter SymbolicExpressionTreeParameter {
get { return (ILookupParameter)Parameters["SymbolicExpressionTree"]; }
}
public ILookupParameter WorldParameter {
get { return (ILookupParameter)Parameters["World"]; }
}
public ILookupParameter MaxTimeStepsParameter {
get { return (ILookupParameter)Parameters["MaxTimeSteps"]; }
}
public IValueLookupParameter SymbolicExpressionTreeGrammarParameter {
get { return (IValueLookupParameter)Parameters["SymbolicExpressionTreeGrammar"]; }
}
// genotype-to-phenotype-mapper:
public ILookupParameter GenotypeToPhenotypeMapperParameter {
get { return (ILookupParameter)Parameters["GenotypeToPhenotypeMapper"]; }
}
public ILookupParameter RandomParameter {
get { return (ILookupParameter)Parameters["Random"]; }
}
public ILookupParameter BoundsParameter {
get { return (ILookupParameter)Parameters["Bounds"]; }
}
public ILookupParameter MaxExpressionLengthParameter {
get { return (ILookupParameter)Parameters["MaximumExpressionLength"]; }
}
#endregion
[StorableConstructor]
protected GEArtificialAntEvaluator(bool deserializing) : base(deserializing) { }
protected GEArtificialAntEvaluator(GEArtificialAntEvaluator original, Cloner cloner) : base(original, cloner) { }
public override IDeepCloneable Clone(Cloner cloner) { return new GEArtificialAntEvaluator(this, cloner); }
public GEArtificialAntEvaluator()
: base() {
Parameters.Add(new LookupParameter("Quality", "The quality of the evaluated artificial ant solution."));
Parameters.Add(new LookupParameter("IntegerVector", "The artificial ant solution encoded as an integer vector genome."));
Parameters.Add(new LookupParameter("SymbolicExpressionTree", "The artificial ant solution encoded as a symbolic expression tree that should be evaluated"));
Parameters.Add(new LookupParameter("World", "The world for the artificial ant with scattered food items."));
Parameters.Add(new LookupParameter("MaxTimeSteps", "The maximal number of time steps that the artificial ant should be simulated."));
Parameters.Add(new ValueLookupParameter("SymbolicExpressionTreeGrammar", "The tree grammar that defines the correct syntax of symbolic expression trees that should be created."));
Parameters.Add(new LookupParameter("GenotypeToPhenotypeMapper", "Maps the genotype (an integer vector) to the phenotype (a symbolic expression tree)."));
Parameters.Add(new LookupParameter("Random", "Random number generator for the genotype creation and the genotype-to-phenotype mapping."));
Parameters.Add(new LookupParameter("Bounds", "The integer number range in which the single genomes of a genotype are created."));
Parameters.Add(new LookupParameter("MaximumExpressionLength", "Maximal length of the expression to control the artificial ant (genotype length)."));
}
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
// BackwardsCompatibility3.3
#region Backwards compatible code, remove with 3.4
if (Parameters.ContainsKey("SymbolicExpressionTree") &&
Parameters["SymbolicExpressionTree"] is ILookupParameter) {
var previousActualName = ((ILookupParameter)Parameters["SymbolicExpressionTree"]).ActualName;
Parameters.Remove("SymbolicExpressionTree");
Parameters.Add(new LookupParameter("SymbolicExpressionTree", "The artificial ant solution encoded as a symbolic expression tree that should be evaluated", previousActualName));
}
#endregion
}
public sealed override IOperation Apply() {
SymbolicExpressionTree tree = GenotypeToPhenotypeMapperParameter.ActualValue.Map(
RandomParameter.ActualValue,
BoundsParameter.ActualValue,
MaxExpressionLengthParameter.ActualValue.Value,
SymbolicExpressionTreeGrammarParameter.ActualValue,
IntegerVectorParameter.ActualValue
);
SymbolicExpressionTreeParameter.ActualValue = tree;
BoolMatrix world = WorldParameter.ActualValue;
IntValue maxTimeSteps = MaxTimeStepsParameter.ActualValue;
AntInterpreter interpreter = new AntInterpreter();
interpreter.MaxTimeSteps = maxTimeSteps.Value;
interpreter.World = world;
interpreter.Expression = tree;
interpreter.Run();
QualityParameter.ActualValue = new DoubleValue(interpreter.FoodEaten);
return null;
}
}
}