[9089] | 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.Operators;
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| 27 | using HeuristicLab.Optimization.Operators;
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| 28 | using HeuristicLab.Parameters;
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| 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 | using HeuristicLab.Selection;
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| 31 | namespace HeuristicLab.Algorithms.LearningClassifierSystems {
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| 32 | /// <summary>
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| 33 | /// An operator which represents the main loop of a genetic algorithm.
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| 34 | /// </summary>
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| 35 | [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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| 36 | [StorableClass]
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| 37 | public sealed class LCSAdaptedGeneticAlgorithm : AlgorithmOperator {
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| 38 | #region Parameter properties
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| 39 | public ValueLookupParameter<IRandom> RandomParameter {
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| 40 | get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
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| 41 | }
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| 42 | public ValueLookupParameter<BoolValue> MaximizationParameter {
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| 43 | get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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| 44 | }
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| 45 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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| 46 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 47 | }
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| 48 | public ValueLookupParameter<IOperator> SelectorParameter {
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| 49 | get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
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| 50 | }
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| 51 | public ValueLookupParameter<IOperator> CrossoverParameter {
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| 52 | get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
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| 53 | }
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[9105] | 54 | public ValueLookupParameter<IOperator> AfterCrossoverParameter {
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| 55 | get { return (ValueLookupParameter<IOperator>)Parameters["AfterCrossover"]; }
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| 56 | }
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[9089] | 57 | public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
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| 58 | get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 59 | }
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| 60 | public ValueLookupParameter<IOperator> MutatorParameter {
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| 61 | get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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| 62 | }
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| 63 | public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
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| 64 | get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
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| 65 | }
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| 66 | public ValueLookupParameter<VariableCollection> ResultsParameter {
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| 67 | get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
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| 68 | }
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| 69 | public ValueLookupParameter<IOperator> AnalyzerParameter {
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| 70 | get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
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| 71 | }
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| 72 | public ValueLookupParameter<IntValue> EvaluatedSolutionsParameter {
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| 73 | get { return (ValueLookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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| 74 | }
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| 75 | public ValueLookupParameter<IntValue> PopulationSizeParameter {
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| 76 | get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
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| 77 | }
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| 78 | private ScopeParameter CurrentScopeParameter {
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| 79 | get { return (ScopeParameter)Parameters["CurrentScope"]; }
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| 80 | }
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| 81 |
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| 82 | public IScope CurrentScope {
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| 83 | get { return CurrentScopeParameter.ActualValue; }
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| 84 | }
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| 85 | #endregion
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| 86 |
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| 87 | [StorableConstructor]
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| 88 | private LCSAdaptedGeneticAlgorithm(bool deserializing) : base(deserializing) { }
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| 89 | private LCSAdaptedGeneticAlgorithm(LCSAdaptedGeneticAlgorithm original, Cloner cloner)
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| 90 | : base(original, cloner) {
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| 91 | }
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| 92 | public override IDeepCloneable Clone(Cloner cloner) {
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| 93 | return new LCSAdaptedGeneticAlgorithm(this, cloner);
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| 94 | }
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| 95 | public LCSAdaptedGeneticAlgorithm()
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| 96 | : base() {
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| 97 | Initialize();
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| 98 | }
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| 99 |
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| 100 | private void Initialize() {
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| 101 | #region Create parameters
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| 102 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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| 103 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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| 104 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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| 105 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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| 106 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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[9105] | 107 | Parameters.Add(new ValueLookupParameter<IOperator>("AfterCrossover", "The operator executed after crossing the solutions."));
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[9089] | 108 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
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| 109 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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| 110 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
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| 111 | Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
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| 112 | Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to analyze each generation."));
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| 113 | Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
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| 114 | Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population."));
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| 115 | 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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| 116 | #endregion
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| 117 |
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| 118 | #region Create operators
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| 119 | VariableCreator variableCreator = new VariableCreator();
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| 120 | ResultsCollector resultsCollector1 = new ResultsCollector();
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| 121 | Placeholder analyzer1 = new Placeholder();
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| 122 | Placeholder selector = new Placeholder();
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| 123 | SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
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| 124 | ChildrenCreator childrenCreator = new ChildrenCreator();
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| 125 | UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
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| 126 | Placeholder crossover = new Placeholder();
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[9105] | 127 | Placeholder afterCrossover = new Placeholder();
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[9089] | 128 | StochasticBranch stochasticBranch = new StochasticBranch();
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| 129 | Placeholder mutator = new Placeholder();
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| 130 | SubScopesRemover subScopesRemover = new SubScopesRemover();
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| 131 | SubScopesCounter subScopesCounter = new SubScopesCounter();
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| 132 | MergingReducer mergingReducer = new MergingReducer();
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| 133 | IntCounter intCounter = new IntCounter();
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| 134 | Comparator comparator = new Comparator();
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| 135 | Placeholder analyzer2 = new Placeholder();
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| 136 | ConditionalBranch conditionalBranch = new ConditionalBranch();
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| 137 |
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| 138 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class GeneticAlgorithm expects this to be called Generations
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| 139 |
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| 140 | resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
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| 141 | resultsCollector1.ResultsParameter.ActualName = "Results";
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| 142 |
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| 143 | analyzer1.Name = "Analyzer";
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| 144 | analyzer1.OperatorParameter.ActualName = "Analyzer";
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| 145 |
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| 146 | selector.Name = "Selector";
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| 147 | selector.OperatorParameter.ActualName = "Selector";
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| 148 |
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| 149 | childrenCreator.ParentsPerChild = new IntValue(2);
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| 150 |
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| 151 | crossover.Name = "Crossover";
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| 152 | crossover.OperatorParameter.ActualName = "Crossover";
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| 153 |
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[9105] | 154 | afterCrossover.Name = "AfterCrossover";
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| 155 | afterCrossover.OperatorParameter.ActualName = "AfterCrossover";
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[9089] | 156 |
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| 157 | stochasticBranch.ProbabilityParameter.ActualName = "MutationProbability";
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| 158 | stochasticBranch.RandomParameter.ActualName = "Random";
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| 159 |
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| 160 | mutator.Name = "Mutator";
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| 161 | mutator.OperatorParameter.ActualName = "Mutator";
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| 162 |
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| 163 | subScopesRemover.RemoveAllSubScopes = true;
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| 164 |
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| 165 | subScopesCounter.Name = "Increment EvaluatedSolutions";
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| 166 | subScopesCounter.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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| 167 |
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| 168 | intCounter.Increment = new IntValue(1);
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| 169 | intCounter.ValueParameter.ActualName = "Generations";
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| 170 |
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| 171 | comparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
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| 172 | comparator.LeftSideParameter.ActualName = "Generations";
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| 173 | comparator.ResultParameter.ActualName = "Terminate";
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| 174 | comparator.RightSideParameter.ActualName = "MaximumGenerations";
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| 175 |
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| 176 | analyzer2.Name = "Analyzer";
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| 177 | analyzer2.OperatorParameter.ActualName = "Analyzer";
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| 178 |
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| 179 | conditionalBranch.ConditionParameter.ActualName = "Terminate";
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| 180 | #endregion
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| 181 |
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| 182 | #region Create operator graph
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| 183 | OperatorGraph.InitialOperator = variableCreator;
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| 184 | variableCreator.Successor = resultsCollector1;
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| 185 | resultsCollector1.Successor = analyzer1;
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| 186 | analyzer1.Successor = selector;
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| 187 | selector.Successor = subScopesProcessor1;
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| 188 | subScopesProcessor1.Operators.Add(new EmptyOperator());
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| 189 | subScopesProcessor1.Operators.Add(childrenCreator);
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[9105] | 190 | subScopesProcessor1.Successor = mergingReducer;
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[9089] | 191 | childrenCreator.Successor = uniformSubScopesProcessor1;
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| 192 | uniformSubScopesProcessor1.Operator = crossover;
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| 193 | uniformSubScopesProcessor1.Successor = subScopesCounter;
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[9105] | 194 | crossover.Successor = afterCrossover;
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| 195 | afterCrossover.Successor = stochasticBranch;
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[9089] | 196 | stochasticBranch.FirstBranch = mutator;
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| 197 | stochasticBranch.SecondBranch = null;
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| 198 | stochasticBranch.Successor = subScopesRemover;
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| 199 | mutator.Successor = null;
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| 200 | subScopesRemover.Successor = null;
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| 201 | subScopesCounter.Successor = null;
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| 202 | mergingReducer.Successor = intCounter;
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| 203 | intCounter.Successor = comparator;
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| 204 | comparator.Successor = analyzer2;
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| 205 | analyzer2.Successor = conditionalBranch;
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| 206 | conditionalBranch.FalseBranch = selector;
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| 207 | conditionalBranch.TrueBranch = null;
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| 208 | conditionalBranch.Successor = null;
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| 209 | #endregion
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| 210 | }
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| 211 |
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| 212 | public override IOperation Apply() {
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| 213 | if (CrossoverParameter.ActualValue == null)
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| 214 | return null;
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| 215 | return base.Apply();
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| 216 | }
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| 217 | }
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| 218 | }
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