1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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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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19 | */
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20 | #endregion
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21 |
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22 |
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23 | using HeuristicLab.Common;
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24 | using HeuristicLab.Core;
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25 | using HeuristicLab.Data;
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26 | using HeuristicLab.Encodings.ConditionActionEncoding;
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27 | using HeuristicLab.Operators;
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28 | using HeuristicLab.Optimization.Operators;
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29 | using HeuristicLab.Parameters;
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30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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31 | using HeuristicLab.Selection;
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32 | namespace HeuristicLab.Algorithms.LearningClassifierSystems {
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33 | /// <summary>
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34 | /// An operator which represents the main loop of a genetic algorithm.
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35 | /// </summary>
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36 | [Item("LCSAdaptedGeneticAlgorithm", "An operator which represents the main loop of a genetic algorithm, which has been adapdet for learning classifier systems.")]
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37 | [StorableClass]
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38 | public sealed class LCSAdaptedGeneticAlgorithm : AlgorithmOperator {
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39 | private const string TEMPID = "TempID";
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40 | private const string SUBSUMEDBY = "SubsumedBy";
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41 | private const string SUBSUMED = "Subsumed";
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42 |
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43 | #region Parameter properties
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44 | public ValueLookupParameter<IRandom> RandomParameter {
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45 | get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
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46 | }
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47 | public ValueLookupParameter<BoolValue> MaximizationParameter {
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48 | get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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49 | }
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50 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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51 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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52 | }
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53 | public ValueLookupParameter<IOperator> SelectorParameter {
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54 | get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
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55 | }
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56 | public ValueLookupParameter<IOperator> AfterCopyingParentsParameter {
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57 | get { return (ValueLookupParameter<IOperator>)Parameters["AfterCopyingParents"]; }
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58 | }
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59 | public ValueLookupParameter<IOperator> CrossoverParameter {
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60 | get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
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61 | }
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62 | public ValueLookupParameter<IOperator> AfterCrossoverParameter {
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63 | get { return (ValueLookupParameter<IOperator>)Parameters["AfterCrossover"]; }
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64 | }
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65 | public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
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66 | get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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67 | }
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68 | public ValueLookupParameter<PercentValue> CrossoverProbabilityParameter {
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69 | get { return (ValueLookupParameter<PercentValue>)Parameters["CrossoverProbability"]; }
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70 | }
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71 | public ValueLookupParameter<IOperator> MutatorParameter {
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72 | get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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73 | }
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74 | public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
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75 | get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
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76 | }
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77 | public ValueLookupParameter<VariableCollection> ResultsParameter {
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78 | get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
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79 | }
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80 | public ValueLookupParameter<IntValue> EvaluatedSolutionsParameter {
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81 | get { return (ValueLookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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82 | }
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83 | public ValueLookupParameter<IntValue> PopulationSizeParameter {
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84 | get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
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85 | }
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86 | public ValueLookupParameter<BoolValue> DoGASubsumptionParameter {
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87 | get { return (ValueLookupParameter<BoolValue>)Parameters["DoGASubsumption"]; }
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88 | }
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89 | private ScopeParameter CurrentScopeParameter {
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90 | get { return (ScopeParameter)Parameters["CurrentScope"]; }
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91 | }
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92 |
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93 | public IScope CurrentScope {
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94 | get { return CurrentScopeParameter.ActualValue; }
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95 | }
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96 | #endregion
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97 |
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98 | [StorableConstructor]
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99 | private LCSAdaptedGeneticAlgorithm(bool deserializing) : base(deserializing) { }
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100 | private LCSAdaptedGeneticAlgorithm(LCSAdaptedGeneticAlgorithm original, Cloner cloner)
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101 | : base(original, cloner) {
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102 | }
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103 | public override IDeepCloneable Clone(Cloner cloner) {
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104 | return new LCSAdaptedGeneticAlgorithm(this, cloner);
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105 | }
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106 | public LCSAdaptedGeneticAlgorithm()
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107 | : base() {
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108 | Initialize();
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109 | }
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110 |
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111 | private void Initialize() {
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112 | #region Create parameters
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113 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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114 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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115 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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116 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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117 | Parameters.Add(new ValueLookupParameter<IOperator>("AfterCopyingParents", "The operator executed after copying a parent instead of using crossover."));
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118 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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119 | Parameters.Add(new ValueLookupParameter<IOperator>("AfterCrossover", "The operator executed after crossing the solutions."));
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120 | Parameters.Add(new ValueLookupParameter<PercentValue>("CrossoverProbability", "The probability that the crossover operator is applied on a solution."));
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121 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that druing the mutation operator a mutation takes place."));
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122 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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123 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
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124 | Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
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125 | Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
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126 | Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population."));
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127 | Parameters.Add(new ValueLookupParameter<BoolValue>("DoGASubsumption", "Sets if GA subsumption is executed."));
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128 | Parameters.Add(new ScopeParameter("CurrentScope", "The current scope which represents a population of solutions on which the genetic algorithm should be applied."));
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129 | #endregion
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130 |
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131 | #region Create operators
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132 | VariableCreator variableCreator = new VariableCreator();
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133 | ResultsCollector resultsCollector1 = new ResultsCollector();
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134 | Placeholder selector = new Placeholder();
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135 | SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
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136 | ChildrenCreator childrenCreator = new ChildrenCreator();
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137 | UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
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138 | StochasticBranch crossoverStochasticBranch = new StochasticBranch();
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139 | RandomSelector randomSelector = new RandomSelector();
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140 | PreservingRightReducer preservingRightReducer = new PreservingRightReducer();
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141 | Placeholder afterCopyingParents = new Placeholder();
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142 | Placeholder crossover = new Placeholder();
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143 | Placeholder afterCrossover = new Placeholder();
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144 | Placeholder mutator = new Placeholder();
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145 | SubScopesRemover subScopesRemover = new SubScopesRemover();
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146 | SubScopesCounter subScopesCounter = new SubScopesCounter();
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147 | MergingReducer mergingReducer = new MergingReducer();
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148 | IntCounter intCounter = new IntCounter();
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149 | Comparator comparator = new Comparator();
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150 | ConditionalBranch conditionalBranch = new ConditionalBranch();
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151 |
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152 | TempSubScopeIDAssigner tempIdAssigner = new TempSubScopeIDAssigner();
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153 | ConditionalBranch doGASubsumptionBranch1 = new ConditionalBranch();
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154 | UniformSubScopesProcessor setSubsumptionFalseSubScopesProcessor = new UniformSubScopesProcessor();
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155 | Assigner setSubsumpByAssigner = new Assigner();
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156 | Assigner setSubsumptionFalseAssigner = new Assigner();
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157 | CheckGASubsumptionOperator checkGASubsumptionOperator = new CheckGASubsumptionOperator();
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158 | ConditionalBranch doGASubsumptionBranch2 = new ConditionalBranch();
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159 | ExecuteGASubsumptionOperator executeGAsubsumptionOperator = new ExecuteGASubsumptionOperator();
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160 | ConditionalSelector subsumptionSelector = new ConditionalSelector();
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161 | LeftReducer subsumptionLeftReducer = new LeftReducer();
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162 |
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163 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class GeneticAlgorithm expects this to be called Generations
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164 |
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165 | //resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Iterations"));
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166 | resultsCollector1.ResultsParameter.ActualName = "Results";
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167 |
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168 | tempIdAssigner.LeftSideParameter.ActualName = TEMPID;
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169 |
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170 | setSubsumpByAssigner.LeftSideParameter.ActualName = SUBSUMEDBY;
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171 | setSubsumpByAssigner.RightSideParameter.Value = new IntValue(-1);
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172 |
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173 | setSubsumptionFalseAssigner.LeftSideParameter.ActualName = SUBSUMED;
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174 | setSubsumptionFalseAssigner.RightSideParameter.Value = new BoolValue(false);
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175 |
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176 | selector.Name = "Selector";
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177 | selector.OperatorParameter.ActualName = "Selector";
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178 |
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179 | childrenCreator.ParentsPerChild = new IntValue(2);
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180 |
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181 | crossoverStochasticBranch.ProbabilityParameter.ActualName = CrossoverProbabilityParameter.ActualName;
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182 | crossoverStochasticBranch.RandomParameter.ActualName = "Random";
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183 |
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184 | randomSelector.CopySelected.Value = true;
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185 | randomSelector.NumberOfSelectedSubScopesParameter.Value = new IntValue(1);
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186 |
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187 | afterCopyingParents.Name = "AfterCopyingParents";
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188 | afterCopyingParents.OperatorParameter.ActualName = "AfterCopyingParents";
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189 |
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190 | crossover.Name = "Crossover";
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191 | crossover.OperatorParameter.ActualName = "Crossover";
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192 |
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193 | afterCrossover.Name = "AfterCrossover";
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194 | afterCrossover.OperatorParameter.ActualName = "AfterCrossover";
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195 |
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196 | mutator.Name = "Mutator";
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197 | mutator.OperatorParameter.ActualName = "Mutator";
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198 |
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199 | doGASubsumptionBranch1.ConditionParameter.ActualName = DoGASubsumptionParameter.ActualName;
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200 |
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201 | checkGASubsumptionOperator.ChildClassifiersParameter.ActualName = "CombinedIntegerVector";
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202 | checkGASubsumptionOperator.ParentsClassifiersParameter.ActualName = "CombinedIntegerVector";
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203 | checkGASubsumptionOperator.NumerositiesParameter.ActualName = "Numerosity";
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204 | checkGASubsumptionOperator.ExperiencesParameter.ActualName = "Experience";
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205 | checkGASubsumptionOperator.ErrorsParameter.ActualName = "Error";
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206 | checkGASubsumptionOperator.TempIDParameter.ActualName = TEMPID;
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207 | checkGASubsumptionOperator.ErrorZeroParameter.ActualName = "ErrorZero";
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208 | checkGASubsumptionOperator.ThetaSubsumptionParameter.ActualName = "ThetaSubsumption";
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209 | checkGASubsumptionOperator.SubsumedByParameter.ActualName = SUBSUMEDBY;
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210 | checkGASubsumptionOperator.SubsumedParameter.ActualName = SUBSUMED;
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211 |
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212 | subScopesRemover.RemoveAllSubScopes = true;
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213 |
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214 | doGASubsumptionBranch2.ConditionParameter.ActualName = DoGASubsumptionParameter.ActualName;
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215 |
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216 | executeGAsubsumptionOperator.NumerositiesParameter.ActualName = "Numerosity";
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217 | executeGAsubsumptionOperator.TempIDParameter.ActualName = TEMPID;
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218 | executeGAsubsumptionOperator.SubsumedByParameter.ActualName = SUBSUMEDBY;
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219 |
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220 | subsumptionSelector.ConditionParameter.ActualName = SUBSUMED;
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221 | subsumptionSelector.CopySelected = new BoolValue(false);
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222 |
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223 | subScopesCounter.Name = "Increment EvaluatedSolutions";
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224 | subScopesCounter.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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225 |
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226 | intCounter.Increment = new IntValue(1);
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227 | intCounter.ValueParameter.ActualName = "Generations";
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228 |
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229 | comparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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230 | comparator.LeftSideParameter.ActualName = "Generations";
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231 | comparator.ResultParameter.ActualName = "Terminate";
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232 | comparator.RightSideParameter.ActualName = "MaximumGenerations";
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233 |
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234 | conditionalBranch.ConditionParameter.ActualName = "Terminate";
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235 | #endregion
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236 |
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237 | #region Create operator graph
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238 | OperatorGraph.InitialOperator = variableCreator;
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239 | variableCreator.Successor = resultsCollector1;
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240 | resultsCollector1.Successor = tempIdAssigner;
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241 | tempIdAssigner.Successor = setSubsumptionFalseSubScopesProcessor;
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242 | setSubsumptionFalseSubScopesProcessor.Operator = setSubsumpByAssigner;
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243 | setSubsumpByAssigner.Successor = setSubsumptionFalseAssigner;
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244 | setSubsumptionFalseAssigner.Successor = null;
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245 | setSubsumptionFalseSubScopesProcessor.Successor = selector;
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246 | selector.Successor = subScopesProcessor1;
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247 | subScopesProcessor1.Operators.Add(new EmptyOperator());
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248 | subScopesProcessor1.Operators.Add(childrenCreator);
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249 | subScopesProcessor1.Successor = mergingReducer;
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250 | childrenCreator.Successor = uniformSubScopesProcessor1;
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251 | uniformSubScopesProcessor1.Operator = crossoverStochasticBranch;
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252 | uniformSubScopesProcessor1.Successor = subScopesCounter;
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253 | crossoverStochasticBranch.FirstBranch = crossover;
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254 | crossoverStochasticBranch.SecondBranch = randomSelector;
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255 | randomSelector.Successor = preservingRightReducer;
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256 | preservingRightReducer.Successor = afterCopyingParents;
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257 | crossoverStochasticBranch.Successor = mutator;
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258 | crossover.Successor = afterCrossover;
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259 | mutator.Successor = doGASubsumptionBranch1;
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260 | doGASubsumptionBranch1.TrueBranch = checkGASubsumptionOperator;
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261 | doGASubsumptionBranch1.FalseBranch = new EmptyOperator();
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262 | doGASubsumptionBranch1.Successor = subScopesRemover;
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263 | subScopesRemover.Successor = null;
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264 | subScopesCounter.Successor = null;
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265 | mergingReducer.Successor = doGASubsumptionBranch2;
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266 | doGASubsumptionBranch2.TrueBranch = executeGAsubsumptionOperator;
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267 | doGASubsumptionBranch2.FalseBranch = new EmptyOperator();
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268 | executeGAsubsumptionOperator.Successor = subsumptionSelector;
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269 | subsumptionSelector.Successor = subsumptionLeftReducer;
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270 | subsumptionLeftReducer.Successor = null;
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271 | doGASubsumptionBranch2.Successor = intCounter;
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272 | intCounter.Successor = comparator;
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273 | comparator.Successor = conditionalBranch;
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274 | conditionalBranch.FalseBranch = selector;
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275 | conditionalBranch.TrueBranch = null;
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276 | conditionalBranch.Successor = null;
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277 | #endregion
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278 | }
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279 |
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280 | public override IOperation Apply() {
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281 | if (CrossoverParameter.ActualValue == null)
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282 | return null;
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283 | return base.Apply();
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284 | }
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285 | }
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286 | }
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