[10071] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[12009] | 3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[10071] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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[10968] | 19 | *
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| 20 | * Author: Sabine Winkler
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[10071] | 21 | */
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| 22 | #endregion
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| 23 |
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| 24 | using HeuristicLab.Common;
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| 25 | using HeuristicLab.Core;
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| 26 | using HeuristicLab.Data;
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| 27 | using HeuristicLab.Encodings.IntegerVectorEncoding;
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| 28 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 29 | using HeuristicLab.Operators;
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| 30 | using HeuristicLab.Optimization;
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| 31 | using HeuristicLab.Parameters;
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| 32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 33 | using HeuristicLab.Problems.ArtificialAnt;
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| 34 | using HeuristicLab.Problems.GrammaticalEvolution.Mappers;
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| 35 |
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| 36 | namespace HeuristicLab.Problems.GrammaticalEvolution {
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[10974] | 37 | [Item("GEArtificialAntEvaluator", "Evaluates an artificial ant solution for grammatical evolution.")]
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[10071] | 38 | [StorableClass]
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| 39 | public class GEArtificialAntEvaluator : SingleSuccessorOperator,
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| 40 | ISingleObjectiveEvaluator, ISymbolicExpressionTreeGrammarBasedOperator {
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| 41 |
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| 42 | #region Parameter Properties
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| 43 | public ILookupParameter<DoubleValue> QualityParameter {
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| 44 | get { return (ILookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 45 | }
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| 46 | // genotype:
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| 47 | public ILookupParameter<IntegerVector> IntegerVectorParameter {
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| 48 | get { return (ILookupParameter<IntegerVector>)Parameters["IntegerVector"]; }
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| 49 | }
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| 50 | // phenotype:
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[12706] | 51 | public ILookupParameter<ISymbolicExpressionTree> SymbolicExpressionTreeParameter {
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| 52 | get { return (ILookupParameter<ISymbolicExpressionTree>)Parameters["SymbolicExpressionTree"]; }
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[10071] | 53 | }
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| 54 | public ILookupParameter<BoolMatrix> WorldParameter {
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| 55 | get { return (ILookupParameter<BoolMatrix>)Parameters["World"]; }
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| 56 | }
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| 57 | public ILookupParameter<IntValue> MaxTimeStepsParameter {
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| 58 | get { return (ILookupParameter<IntValue>)Parameters["MaxTimeSteps"]; }
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| 59 | }
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| 60 | public IValueLookupParameter<ISymbolicExpressionGrammar> SymbolicExpressionTreeGrammarParameter {
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| 61 | get { return (IValueLookupParameter<ISymbolicExpressionGrammar>)Parameters["SymbolicExpressionTreeGrammar"]; }
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| 62 | }
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| 63 | // genotype-to-phenotype-mapper:
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| 64 | public ILookupParameter<IGenotypeToPhenotypeMapper> GenotypeToPhenotypeMapperParameter {
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| 65 | get { return (ILookupParameter<IGenotypeToPhenotypeMapper>)Parameters["GenotypeToPhenotypeMapper"]; }
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| 66 | }
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[10280] | 67 | public ILookupParameter<IRandom> RandomParameter {
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| 68 | get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
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| 69 | }
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[10290] | 70 | public ILookupParameter<IntMatrix> BoundsParameter {
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| 71 | get { return (ILookupParameter<IntMatrix>)Parameters["Bounds"]; }
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| 72 | }
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| 73 | public ILookupParameter<IntValue> MaxExpressionLengthParameter {
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| 74 | get { return (ILookupParameter<IntValue>)Parameters["MaximumExpressionLength"]; }
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| 75 | }
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[10071] | 76 | #endregion
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| 77 |
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| 78 | [StorableConstructor]
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| 79 | protected GEArtificialAntEvaluator(bool deserializing) : base(deserializing) { }
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| 80 | protected GEArtificialAntEvaluator(GEArtificialAntEvaluator original, Cloner cloner) : base(original, cloner) { }
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| 81 | public override IDeepCloneable Clone(Cloner cloner) { return new GEArtificialAntEvaluator(this, cloner); }
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| 82 | public GEArtificialAntEvaluator()
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| 83 | : base() {
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| 84 | Parameters.Add(new LookupParameter<DoubleValue>("Quality", "The quality of the evaluated artificial ant solution."));
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| 85 | Parameters.Add(new LookupParameter<IntegerVector>("IntegerVector", "The artificial ant solution encoded as an integer vector genome."));
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[12706] | 86 | Parameters.Add(new LookupParameter<ISymbolicExpressionTree>("SymbolicExpressionTree", "The artificial ant solution encoded as a symbolic expression tree that should be evaluated"));
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[10071] | 87 | Parameters.Add(new LookupParameter<BoolMatrix>("World", "The world for the artificial ant with scattered food items."));
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| 88 | Parameters.Add(new LookupParameter<IntValue>("MaxTimeSteps", "The maximal number of time steps that the artificial ant should be simulated."));
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| 89 | Parameters.Add(new ValueLookupParameter<ISymbolicExpressionGrammar>("SymbolicExpressionTreeGrammar", "The tree grammar that defines the correct syntax of symbolic expression trees that should be created."));
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| 90 | Parameters.Add(new LookupParameter<IGenotypeToPhenotypeMapper>("GenotypeToPhenotypeMapper", "Maps the genotype (an integer vector) to the phenotype (a symbolic expression tree)."));
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[10280] | 91 | Parameters.Add(new LookupParameter<IRandom>("Random", "Random number generator for the genotype creation and the genotype-to-phenotype mapping."));
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[10290] | 92 |
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| 93 | Parameters.Add(new LookupParameter<IntMatrix>("Bounds", "The integer number range in which the single genomes of a genotype are created."));
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[10328] | 94 | Parameters.Add(new LookupParameter<IntValue>("MaximumExpressionLength", "Maximal length of the expression to control the artificial ant (genotype length)."));
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[10071] | 95 | }
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| 96 |
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[12706] | 97 | [StorableHook(HookType.AfterDeserialization)]
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| 98 | private void AfterDeserialization() {
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| 99 | // BackwardsCompatibility3.3
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| 100 | #region Backwards compatible code, remove with 3.4
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| 101 |
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| 102 | if (Parameters.ContainsKey("SymbolicExpressionTree") &&
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| 103 | Parameters["SymbolicExpressionTree"] is ILookupParameter<SymbolicExpressionTree>) {
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| 104 | var previousActualName = ((ILookupParameter<SymbolicExpressionTree>)Parameters["SymbolicExpressionTree"]).ActualName;
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| 105 | Parameters.Remove("SymbolicExpressionTree");
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| 106 | Parameters.Add(new LookupParameter<ISymbolicExpressionTree>("SymbolicExpressionTree", "The artificial ant solution encoded as a symbolic expression tree that should be evaluated", previousActualName));
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| 107 | }
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| 108 |
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| 109 | #endregion
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| 110 |
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| 111 | }
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| 112 |
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[10071] | 113 | public sealed override IOperation Apply() {
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[10280] | 114 | SymbolicExpressionTree tree = GenotypeToPhenotypeMapperParameter.ActualValue.Map(
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| 115 | RandomParameter.ActualValue,
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[10290] | 116 | BoundsParameter.ActualValue,
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| 117 | MaxExpressionLengthParameter.ActualValue.Value,
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[10071] | 118 | SymbolicExpressionTreeGrammarParameter.ActualValue,
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| 119 | IntegerVectorParameter.ActualValue
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| 120 | );
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[10280] | 121 | SymbolicExpressionTreeParameter.ActualValue = tree;
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[10071] | 122 | BoolMatrix world = WorldParameter.ActualValue;
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| 123 | IntValue maxTimeSteps = MaxTimeStepsParameter.ActualValue;
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| 124 |
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| 125 | AntInterpreter interpreter = new AntInterpreter();
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| 126 | interpreter.MaxTimeSteps = maxTimeSteps.Value;
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| 127 | interpreter.World = world;
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[10280] | 128 | interpreter.Expression = tree;
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[10071] | 129 | interpreter.Run();
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| 130 |
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| 131 | QualityParameter.ActualValue = new DoubleValue(interpreter.FoodEaten);
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| 132 | return null;
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| 133 | }
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| 134 | }
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| 135 | } |
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