#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; } } }