| 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> CrossoverParameter {
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| 57 | get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
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| 58 | }
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| 59 | public ValueLookupParameter<IOperator> AfterCrossoverParameter {
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| 60 | get { return (ValueLookupParameter<IOperator>)Parameters["AfterCrossover"]; }
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| 61 | }
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| 62 | public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
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| 63 | get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 64 | }
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| 65 | public ValueLookupParameter<PercentValue> CrossoverProbabilityParameter {
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| 66 | get { return (ValueLookupParameter<PercentValue>)Parameters["CrossoverProbability"]; }
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| 67 | }
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| 68 | public ValueLookupParameter<IOperator> MutatorParameter {
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| 69 | get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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| 70 | }
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| 71 | public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
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| 72 | get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
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| 73 | }
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| 74 | public ValueLookupParameter<VariableCollection> ResultsParameter {
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| 75 | get { return (ValueLookupParameter<VariableCollection>)Parameters["Results"]; }
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| 76 | }
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| 77 | public ValueLookupParameter<IntValue> EvaluatedSolutionsParameter {
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| 78 | get { return (ValueLookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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| 79 | }
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| 80 | public ValueLookupParameter<IntValue> PopulationSizeParameter {
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| 81 | get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
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| 82 | }
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| 83 | public ValueLookupParameter<BoolValue> DoGASubsumptionParameter {
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| 84 | get { return (ValueLookupParameter<BoolValue>)Parameters["DoGASubsumption"]; }
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| 85 | }
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| 86 | private ScopeParameter CurrentScopeParameter {
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| 87 | get { return (ScopeParameter)Parameters["CurrentScope"]; }
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| 88 | }
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| 89 |
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| 90 | public IScope CurrentScope {
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| 91 | get { return CurrentScopeParameter.ActualValue; }
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| 92 | }
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| 93 | #endregion
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| 94 |
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| 95 | [StorableConstructor]
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| 96 | private LCSAdaptedGeneticAlgorithm(bool deserializing) : base(deserializing) { }
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| 97 | private LCSAdaptedGeneticAlgorithm(LCSAdaptedGeneticAlgorithm original, Cloner cloner)
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| 98 | : base(original, cloner) {
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| 99 | }
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| 100 | public override IDeepCloneable Clone(Cloner cloner) {
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| 101 | return new LCSAdaptedGeneticAlgorithm(this, cloner);
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| 102 | }
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| 103 | public LCSAdaptedGeneticAlgorithm()
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| 104 | : base() {
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| 105 | Initialize();
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| 106 | }
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| 107 |
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| 108 | private void Initialize() {
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| 109 | #region Create parameters
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| 110 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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| 111 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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| 112 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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| 113 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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| 114 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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| 115 | Parameters.Add(new ValueLookupParameter<IOperator>("AfterCrossover", "The operator executed after crossing the solutions."));
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| 116 | Parameters.Add(new ValueLookupParameter<PercentValue>("CrossoverProbability", "The probability that the crossover operator is applied on a solution."));
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| 117 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that druing the mutation operator a mutation takes place."));
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| 118 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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| 119 | Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations which should be processed."));
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| 120 | Parameters.Add(new ValueLookupParameter<VariableCollection>("Results", "The variable collection where results should be stored."));
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| 121 | Parameters.Add(new ValueLookupParameter<IntValue>("EvaluatedSolutions", "The number of times solutions have been evaluated."));
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| 122 | Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population."));
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| 123 | Parameters.Add(new ValueLookupParameter<BoolValue>("DoGASubsumption", "Sets if GA subsumption is executed."));
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| 124 | 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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| 125 | #endregion
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| 126 |
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| 127 | #region Create operators
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| 128 | VariableCreator variableCreator = new VariableCreator();
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| 129 | ResultsCollector resultsCollector1 = new ResultsCollector();
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| 130 | Placeholder selector = new Placeholder();
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| 131 | SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
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| 132 | ChildrenCreator childrenCreator = new ChildrenCreator();
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| 133 | UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
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| 134 | StochasticBranch crossoverStochasticBranch = new StochasticBranch();
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| 135 | RandomSelector randomSelector = new RandomSelector();
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| 136 | PreservingRightReducer preservingRightReducer = new PreservingRightReducer();
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| 137 | Assigner numerosityAssigner = new Assigner();
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| 138 | Assigner experienceAssigner = new Assigner();
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| 139 | Placeholder crossover = new Placeholder();
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| 140 | Placeholder afterCrossover = new Placeholder();
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| 141 | Placeholder mutator = new Placeholder();
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| 142 | SubScopesRemover subScopesRemover = new SubScopesRemover();
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| 143 | SubScopesCounter subScopesCounter = new SubScopesCounter();
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| 144 | MergingReducer mergingReducer = new MergingReducer();
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| 145 | IntCounter intCounter = new IntCounter();
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| 146 | Comparator comparator = new Comparator();
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| 147 | ConditionalBranch conditionalBranch = new ConditionalBranch();
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| 148 |
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| 149 | TempSubScopeIDAssigner tempIdAssigner = new TempSubScopeIDAssigner();
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| 150 | ConditionalBranch doGASubsumptionBranch1 = new ConditionalBranch();
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| 151 | UniformSubScopesProcessor setSubsumptionFalseSubScopesProcessor = new UniformSubScopesProcessor();
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| 152 | Assigner setSubsumpByAssigner = new Assigner();
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| 153 | Assigner setSubsumptionFalseAssigner = new Assigner();
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| 154 | CheckGASubsumptionOperator checkGASubsumptionOperator = new CheckGASubsumptionOperator();
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| 155 | ConditionalBranch doGASubsumptionBranch2 = new ConditionalBranch();
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| 156 | ExecuteGASubsumptionOperator executeGAsubsumptionOperator = new ExecuteGASubsumptionOperator();
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| 157 | ConditionalSelector subsumptionSelector = new ConditionalSelector();
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| 158 | LeftReducer subsumptionLeftReducer = new LeftReducer();
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| 159 |
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| 160 | variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class GeneticAlgorithm expects this to be called Generations
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| 161 |
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| 162 | //resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Iterations"));
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| 163 | resultsCollector1.ResultsParameter.ActualName = "Results";
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| 164 |
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| 165 | tempIdAssigner.LeftSideParameter.ActualName = TEMPID;
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| 166 |
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| 167 | setSubsumpByAssigner.LeftSideParameter.ActualName = SUBSUMEDBY;
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| 168 | setSubsumpByAssigner.RightSideParameter.Value = new IntValue(-1);
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| 169 |
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| 170 | setSubsumptionFalseAssigner.LeftSideParameter.ActualName = SUBSUMED;
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| 171 | setSubsumptionFalseAssigner.RightSideParameter.Value = new BoolValue(false);
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| 172 |
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| 173 | selector.Name = "Selector";
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| 174 | selector.OperatorParameter.ActualName = "Selector";
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| 175 |
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| 176 | childrenCreator.ParentsPerChild = new IntValue(2);
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| 177 |
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| 178 | crossoverStochasticBranch.ProbabilityParameter.ActualName = CrossoverProbabilityParameter.ActualName;
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| 179 | crossoverStochasticBranch.RandomParameter.ActualName = "Random";
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| 180 |
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| 181 | randomSelector.CopySelected.Value = true;
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| 182 | randomSelector.NumberOfSelectedSubScopesParameter.Value = new IntValue(1);
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| 183 |
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| 184 | crossover.Name = "Crossover";
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| 185 | crossover.OperatorParameter.ActualName = "Crossover";
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| 186 |
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| 187 | numerosityAssigner.LeftSideParameter.ActualName = "Numerosity";
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| 188 | numerosityAssigner.RightSideParameter.Value = new IntValue(1);
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| 189 |
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| 190 | experienceAssigner.LeftSideParameter.ActualName = "Experience";
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| 191 | experienceAssigner.RightSideParameter.Value = new IntValue(0);
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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 = numerosityAssigner;
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| 257 | numerosityAssigner.Successor = experienceAssigner;
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| 258 | experienceAssigner.Successor = null;
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| 259 | crossoverStochasticBranch.Successor = mutator;
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| 260 | crossover.Successor = afterCrossover;
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| 261 | mutator.Successor = doGASubsumptionBranch1;
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| 262 | doGASubsumptionBranch1.TrueBranch = checkGASubsumptionOperator;
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| 263 | doGASubsumptionBranch1.FalseBranch = new EmptyOperator();
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| 264 | doGASubsumptionBranch1.Successor = subScopesRemover;
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| 265 | subScopesRemover.Successor = null;
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| 266 | subScopesCounter.Successor = null;
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| 267 | mergingReducer.Successor = doGASubsumptionBranch2;
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| 268 | doGASubsumptionBranch2.TrueBranch = executeGAsubsumptionOperator;
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| 269 | doGASubsumptionBranch2.FalseBranch = new EmptyOperator();
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| 270 | executeGAsubsumptionOperator.Successor = subsumptionSelector;
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| 271 | subsumptionSelector.Successor = subsumptionLeftReducer;
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| 272 | subsumptionLeftReducer.Successor = null;
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| 273 | doGASubsumptionBranch2.Successor = intCounter;
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| 274 | intCounter.Successor = comparator;
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| 275 | comparator.Successor = conditionalBranch;
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| 276 | conditionalBranch.FalseBranch = selector;
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| 277 | conditionalBranch.TrueBranch = null;
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| 278 | conditionalBranch.Successor = null;
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| 279 | #endregion
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| 280 | }
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| 281 |
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| 282 | public override IOperation Apply() {
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| 283 | if (CrossoverParameter.ActualValue == null)
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| 284 | return null;
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| 285 | return base.Apply();
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| 286 | }
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| 287 | }
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| 288 | }
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