| 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 | using System;
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| 23 | using System.Linq;
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| 24 | using HeuristicLab.Analysis;
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| 25 | using HeuristicLab.Common;
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| 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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| 28 | using HeuristicLab.Encodings.ConditionActionEncoding;
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| 29 | using HeuristicLab.Operators;
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| 30 | using HeuristicLab.Optimization;
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| 31 | using HeuristicLab.Optimization.Operators;
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| 32 | using HeuristicLab.Parameters;
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| 33 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 34 | using HeuristicLab.Random;
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| 35 |
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| 36 | namespace HeuristicLab.Algorithms.LearningClassifierSystems {
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| 37 | /// <summary>
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| 38 | /// A learning classifier system.
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| 39 | /// </summary>
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| 40 | [Item("XCS", "A learning classifier system")]
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| 41 | [Creatable("Algorithms")]
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| 42 | [StorableClass]
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| 43 | public sealed class LearningClassifierSystem : HeuristicOptimizationEngineAlgorithm, IStorableContent {
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| 44 | public string Filename { get; set; }
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| 45 |
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| 46 | #region Problem Properties
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| 47 | public override Type ProblemType {
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| 48 | get { return typeof(IConditionActionProblem); }
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| 49 | }
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| 50 | public new IConditionActionProblem Problem {
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| 51 | get { return (IConditionActionProblem)base.Problem; }
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| 52 | set { base.Problem = value; }
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| 53 | }
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| 54 | #endregion
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| 55 |
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| 56 | #region Parameter Properties
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| 57 | private ValueParameter<IntValue> SeedParameter {
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| 58 | get { return (ValueParameter<IntValue>)Parameters["Seed"]; }
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| 59 | }
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| 60 | private ValueParameter<BoolValue> SetSeedRandomlyParameter {
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| 61 | get { return (ValueParameter<BoolValue>)Parameters["SetSeedRandomly"]; }
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| 62 | }
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| 63 | private ValueParameter<BoolValue> CreateInitialPopulationParameter {
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| 64 | get { return (ValueParameter<BoolValue>)Parameters["CreateInitialPopulation"]; }
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| 65 | }
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| 66 | private ValueParameter<IntValue> PopulationSizeParameter {
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| 67 | get { return (ValueParameter<IntValue>)Parameters["N"]; }
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| 68 | }
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| 69 | private ValueParameter<PercentValue> BetaParameter {
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| 70 | get { return (ValueParameter<PercentValue>)Parameters["Beta"]; }
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| 71 | }
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| 72 | private ValueParameter<PercentValue> AlphaParameter {
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| 73 | get { return (ValueParameter<PercentValue>)Parameters["Alpha"]; }
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| 74 | }
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| 75 | private ValueParameter<DoubleValue> ErrorZeroParameter {
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| 76 | get { return (ValueParameter<DoubleValue>)Parameters["ErrorZero"]; }
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| 77 | }
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| 78 | private ValueParameter<DoubleValue> PowerParameter {
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| 79 | get { return (ValueParameter<DoubleValue>)Parameters["v"]; }
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| 80 | }
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| 81 | private ValueParameter<PercentValue> GammaParameter {
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| 82 | get { return (ValueParameter<PercentValue>)Parameters["Gamma"]; }
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| 83 | }
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| 84 | private ValueParameter<PercentValue> CrossoverProbabilityParameter {
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| 85 | get { return (ValueParameter<PercentValue>)Parameters["CrossoverProbability"]; }
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| 86 | }
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| 87 | private ValueParameter<PercentValue> MutationProbabilityParameter {
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| 88 | get { return (ValueParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 89 | }
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| 90 | private ValueParameter<IntValue> ThetaGAParameter {
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| 91 | get { return (ValueParameter<IntValue>)Parameters["ThetaGA"]; }
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| 92 | }
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| 93 | private ValueParameter<IntValue> ThetaDeletionParameter {
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| 94 | get { return (ValueParameter<IntValue>)Parameters["ThetaDeletion"]; }
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| 95 | }
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| 96 | private ValueParameter<IntValue> ThetaSubsumptionParameter {
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| 97 | get { return (ValueParameter<IntValue>)Parameters["ThetaSubsumption"]; }
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| 98 | }
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| 99 | private ValueParameter<PercentValue> DeltaParameter {
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| 100 | get { return (ValueParameter<PercentValue>)Parameters["Delta"]; }
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| 101 | }
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| 102 | private ValueParameter<PercentValue> ExplorationProbabilityParameter {
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| 103 | get { return (ValueParameter<PercentValue>)Parameters["ExplorationProbability"]; }
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| 104 | }
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| 105 | private ValueParameter<BoolValue> DoGASubsumptionParameter {
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| 106 | get { return (ValueParameter<BoolValue>)Parameters["DoGASubsumption"]; }
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| 107 | }
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| 108 | private ValueParameter<BoolValue> DoActionSetSubsumptionParameter {
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| 109 | get { return (ValueParameter<BoolValue>)Parameters["DoActionSetSubsumption"]; }
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| 110 | }
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| 111 | private ValueParameter<MultiAnalyzer> AnalyzerParameter {
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| 112 | get { return (ValueParameter<MultiAnalyzer>)Parameters["Analyzer"]; }
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| 113 | }
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| 114 | private ValueParameter<MultiAnalyzer> FinalAnalyzerParameter {
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| 115 | get { return (ValueParameter<MultiAnalyzer>)Parameters["FinalAnalyzer"]; }
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| 116 | }
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| 117 | private ValueParameter<IntValue> MaxIterationsParameter {
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| 118 | get { return (ValueParameter<IntValue>)Parameters["MaxIterations"]; }
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| 119 | }
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| 120 | public IConstrainedValueParameter<ISelector> SelectorParameter {
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| 121 | get { return (IConstrainedValueParameter<ISelector>)Parameters["Selector"]; }
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| 122 | }
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| 123 | public IConstrainedValueParameter<ICrossover> CrossoverParameter {
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| 124 | get { return (IConstrainedValueParameter<ICrossover>)Parameters["Crossover"]; }
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| 125 | }
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| 126 | public IConstrainedValueParameter<IManipulator> MutatorParameter {
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| 127 | get { return (IConstrainedValueParameter<IManipulator>)Parameters["Mutator"]; }
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| 128 | }
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| 129 | public ValueParameter<IntValue> AnalyzeInIterationParameter {
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| 130 | get { return (ValueParameter<IntValue>)Parameters["AnalyzeInIteration"]; }
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| 131 | }
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| 132 | #endregion
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| 133 |
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| 134 | #region Properties
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| 135 | public IntValue Seed {
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| 136 | get { return SeedParameter.Value; }
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| 137 | set { SeedParameter.Value = value; }
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| 138 | }
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| 139 | public BoolValue SetSeedRandomly {
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| 140 | get { return SetSeedRandomlyParameter.Value; }
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| 141 | set { SetSeedRandomlyParameter.Value = value; }
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| 142 | }
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| 143 | public BoolValue CreateInitialPopulation {
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| 144 | get { return CreateInitialPopulationParameter.Value; }
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| 145 | set { CreateInitialPopulationParameter.Value = value; }
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| 146 | }
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| 147 | public IntValue PopulationSize {
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| 148 | get { return PopulationSizeParameter.Value; }
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| 149 | set { PopulationSizeParameter.Value = value; }
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| 150 | }
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| 151 | public PercentValue Beta {
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| 152 | get { return BetaParameter.Value; }
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| 153 | set { BetaParameter.Value = value; }
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| 154 | }
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| 155 | public PercentValue Alpha {
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| 156 | get { return AlphaParameter.Value; }
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| 157 | set { AlphaParameter.Value = value; }
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| 158 | }
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| 159 | public DoubleValue ErrorZero {
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| 160 | get { return ErrorZeroParameter.Value; }
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| 161 | set { ErrorZeroParameter.Value = value; }
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| 162 | }
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| 163 | public DoubleValue Power {
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| 164 | get { return PowerParameter.Value; }
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| 165 | set { PowerParameter.Value = value; }
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| 166 | }
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| 167 | public PercentValue Gamma {
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| 168 | get { return GammaParameter.Value; }
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| 169 | set { GammaParameter.Value = value; }
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| 170 | }
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| 171 | public PercentValue CrossoverProbability {
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| 172 | get { return CrossoverProbabilityParameter.Value; }
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| 173 | set { CrossoverProbabilityParameter.Value = value; }
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| 174 | }
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| 175 | public PercentValue MutationProbability {
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| 176 | get { return MutationProbabilityParameter.Value; }
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| 177 | set { MutationProbabilityParameter.Value = value; }
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| 178 | }
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| 179 | public IntValue ThetaGA {
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| 180 | get { return ThetaGAParameter.Value; }
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| 181 | set { ThetaGAParameter.Value = value; }
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| 182 | }
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| 183 | public IntValue ThetaDeletion {
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| 184 | get { return ThetaDeletionParameter.Value; }
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| 185 | set { ThetaDeletionParameter.Value = value; }
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| 186 | }
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| 187 | public IntValue ThetaSubsumption {
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| 188 | get { return ThetaSubsumptionParameter.Value; }
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| 189 | set { ThetaSubsumptionParameter.Value = value; }
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| 190 | }
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| 191 | public PercentValue Delta {
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| 192 | get { return DeltaParameter.Value; }
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| 193 | set { DeltaParameter.Value = value; }
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| 194 | }
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| 195 | public PercentValue ExplorationProbability {
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| 196 | get { return ExplorationProbabilityParameter.Value; }
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| 197 | set { ExplorationProbabilityParameter.Value = value; }
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| 198 | }
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| 199 | public BoolValue DoGASubsumption {
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| 200 | get { return DoGASubsumptionParameter.Value; }
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| 201 | set { DoGASubsumptionParameter.Value = value; }
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| 202 | }
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| 203 | public BoolValue DoActionSetSubsumption {
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| 204 | get { return DoActionSetSubsumptionParameter.Value; }
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| 205 | set { DoActionSetSubsumptionParameter.Value = value; }
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| 206 | }
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| 207 | public IntValue MaxIterations {
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| 208 | get { return MaxIterationsParameter.Value; }
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| 209 | set { MaxIterationsParameter.Value = value; }
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| 210 | }
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| 211 | public MultiAnalyzer Analyzer {
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| 212 | get { return AnalyzerParameter.Value; }
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| 213 | set { AnalyzerParameter.Value = value; }
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| 214 | }
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| 215 | public MultiAnalyzer FinalAnalyzer {
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| 216 | get { return FinalAnalyzerParameter.Value; }
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| 217 | set { FinalAnalyzerParameter.Value = value; }
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| 218 | }
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| 219 | public ISelector Selector {
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| 220 | get { return SelectorParameter.Value; }
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| 221 | set { SelectorParameter.Value = value; }
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| 222 | }
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| 223 | public ICrossover Crossover {
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| 224 | get { return CrossoverParameter.Value; }
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| 225 | set { CrossoverParameter.Value = value; }
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| 226 | }
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| 227 | public IManipulator Mutator {
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| 228 | get { return MutatorParameter.Value; }
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| 229 | set { MutatorParameter.Value = value; }
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| 230 | }
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| 231 | private RandomCreator RandomCreator {
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| 232 | get { return (RandomCreator)OperatorGraph.InitialOperator; }
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| 233 | }
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| 234 | public LearningClassifierSystemMainLoop MainLoop {
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| 235 | get { return FindMainLoop(RandomCreator.Successor); }
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| 236 | }
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| 237 | #endregion
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| 238 |
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| 239 | public LearningClassifierSystem()
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| 240 | : base() {
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| 241 | #region Create parameters
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| 242 | Parameters.Add(new ValueParameter<IntValue>("Seed", "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
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| 243 | Parameters.Add(new ValueParameter<BoolValue>("SetSeedRandomly", "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
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| 244 | Parameters.Add(new ValueParameter<BoolValue>("CreateInitialPopulation", "Specifies if a population should be created at the beginning of the algorithm.", new BoolValue(false)));
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| 245 | Parameters.Add(new ValueParameter<IntValue>("N", "Max size of the population of solutions.", new IntValue(100)));
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| 246 | Parameters.Add(new ValueParameter<PercentValue>("Beta", "Learning rate", new PercentValue(0.1)));
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| 247 | Parameters.Add(new ValueParameter<PercentValue>("Alpha", "", new PercentValue(0.1)));
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| 248 | Parameters.Add(new ValueParameter<DoubleValue>("ErrorZero", "The error below which classifiers are considered to have equal accuracy", new DoubleValue(10)));
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| 249 | Parameters.Add(new ValueParameter<DoubleValue>("v", "Power parameter", new DoubleValue(5)));
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| 250 | Parameters.Add(new ValueParameter<PercentValue>("Gamma", "Discount factor", new PercentValue(0.71)));
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| 251 | Parameters.Add(new ValueParameter<PercentValue>("CrossoverProbability", "Probability of crossover", new PercentValue(0.9)));
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| 252 | Parameters.Add(new ValueParameter<PercentValue>("MutationProbability", "Probability of mutation", new PercentValue(0.05)));
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| 253 | Parameters.Add(new ValueParameter<IntValue>("ThetaGA", "GA threshold. GA is applied in a set when the average time since the last GA is greater than ThetaGA.", new IntValue(25)));
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| 254 | Parameters.Add(new ValueParameter<IntValue>("ThetaDeletion", "Deletion threshold. If the experience of a classifier is greater than ThetaDeletion, its fitness may be considered in its probability of deletion.", new IntValue(20)));
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| 255 | Parameters.Add(new ValueParameter<IntValue>("ThetaSubsumption", "Subsumption threshold. The experience of a classifier must be greater than TheatSubsumption to be able to subsume another classifier.", new IntValue(20)));
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| 256 | Parameters.Add(new ValueParameter<PercentValue>("Delta", "Delta specifies the fraction of mean fitness in [P] below which the fitness of a classifier may be considered in its probability of deletion", new PercentValue(0.1)));
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| 257 | Parameters.Add(new ValueParameter<PercentValue>("ExplorationProbability", "Probability of selecting the action uniform randomly", new PercentValue(0.5)));
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| 258 | Parameters.Add(new ValueParameter<BoolValue>("DoGASubsumption", "Specifies if offsprings are tested for possible logical subsumption by parents.", new BoolValue(true)));
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| 259 | Parameters.Add(new ValueParameter<BoolValue>("DoActionSetSubsumption", "Specifies if action set is tested for subsuming classifiers.", new BoolValue(true)));
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| 260 | Parameters.Add(new ValueParameter<MultiAnalyzer>("Analyzer", "The operator used to analyze each generation.", new MultiAnalyzer()));
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| 261 | Parameters.Add(new ValueParameter<MultiAnalyzer>("FinalAnalyzer", "The operator used to analyze the last generation.", new MultiAnalyzer()));
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| 262 | Parameters.Add(new ValueParameter<IntValue>("MaxIterations", "The maximum number of iterations.", new IntValue(1000)));
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| 263 | Parameters.Add(new ConstrainedValueParameter<ISelector>("Selector", "The operator used to select solutions."));
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| 264 | Parameters.Add(new ConstrainedValueParameter<ICrossover>("Crossover", "The operator used to cross solutions."));
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| 265 | Parameters.Add(new ConstrainedValueParameter<IManipulator>("Mutator", "The operator used to mutate solutions."));
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| 266 | Parameters.Add(new ValueParameter<IntValue>("AnalyzeInIteration", "", new IntValue(50)));
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| 267 | #endregion
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| 268 |
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| 269 | #region Create operators
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| 270 | RandomCreator randomCreator = new RandomCreator();
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| 271 |
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| 272 | ResultsCollector resultsCollector = new ResultsCollector();
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| 273 | LearningClassifierSystemMainLoop mainLoop = new LearningClassifierSystemMainLoop();
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| 274 |
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| 275 | randomCreator.RandomParameter.ActualName = "Random";
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| 276 | randomCreator.SeedParameter.ActualName = SeedParameter.Name;
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| 277 | randomCreator.SeedParameter.Value = null;
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| 278 | randomCreator.SetSeedRandomlyParameter.ActualName = SetSeedRandomlyParameter.Name;
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| 279 | randomCreator.SetSeedRandomlyParameter.Value = null;
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| 280 |
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| 281 | resultsCollector.ResultsParameter.ActualName = "Results";
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| 282 |
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| 283 | mainLoop.AnalyzerParameter.ActualName = AnalyzerParameter.Name;
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| 284 | mainLoop.FinalAnalyzerParameter.ActualName = FinalAnalyzerParameter.Name;
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| 285 | mainLoop.MaxIterationsParameter.ActualName = MaxIterationsParameter.Name;
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| 286 | mainLoop.SelectorParameter.ActualName = SelectorParameter.Name;
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| 287 | mainLoop.CrossoverParameter.ActualName = CrossoverParameter.Name;
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| 288 | mainLoop.MutatorParameter.ActualName = MutatorParameter.Name;
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| 289 | mainLoop.CrossoverProbabilityParameter.ActualName = CrossoverProbabilityParameter.Name;
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| 290 | mainLoop.AnalyzeInIterationParameter.ActualName = AnalyzeInIterationParameter.Name;
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| 291 | #endregion
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| 292 |
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| 293 | #region Create operator graph
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| 294 | OperatorGraph.InitialOperator = randomCreator;
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| 295 | randomCreator.Successor = resultsCollector;
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| 296 | resultsCollector.Successor = mainLoop;
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| 297 | #endregion
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| 298 |
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| 299 | UpdateAnalyzers();
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| 300 | }
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| 301 | private LearningClassifierSystem(LearningClassifierSystem original, Cloner cloner)
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| 302 | : base(original, cloner) {
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| 303 | }
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| 304 | public override IDeepCloneable Clone(Cloner cloner) {
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| 305 | return new LearningClassifierSystem(this, cloner);
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| 306 | }
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| 307 | [StorableConstructor]
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| 308 | private LearningClassifierSystem(bool deserializing) : base(deserializing) { }
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| 309 |
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| 310 | protected override void OnProblemChanged() {
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| 311 | if (Problem != null) {
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| 312 | ParameterizeEvaluator(Problem.Evaluator);
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| 313 | MainLoop.SetCurrentProblem(Problem);
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| 314 | UpdateSelectors();
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| 315 | UpdateCrossovers();
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| 316 | UpdateMutators();
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| 317 | UpdateAnalyzers();
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| 318 | ParameterizeSelectors();
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| 319 | ParameterizeManipulator();
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| 320 | }
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| 321 | base.OnProblemChanged();
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| 322 | }
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| 323 |
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| 324 | protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
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| 325 | ParameterizeEvaluator(Problem.Evaluator);
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| 326 | MainLoop.SetCurrentProblem(Problem);
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| 327 | base.Problem_EvaluatorChanged(sender, e);
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| 328 | }
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| 329 | protected override void Problem_SolutionCreatorChanged(object sender, EventArgs e) {
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| 330 | MainLoop.SetCurrentProblem(Problem);
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| 331 | base.Problem_SolutionCreatorChanged(sender, e);
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| 332 | }
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| 333 | protected override void Problem_OperatorsChanged(object sender, EventArgs e) {
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| 334 | UpdateSelectors();
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| 335 | UpdateCrossovers();
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| 336 | UpdateMutators();
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| 337 | UpdateAnalyzers();
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| 338 | ParameterizeSelectors();
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| 339 | ParameterizeManipulator();
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| 340 | base.Problem_OperatorsChanged(sender, e);
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| 341 | }
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| 342 |
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| 343 | private void ParameterizeSelectors() {
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| 344 | foreach (ISelector selector in SelectorParameter.ValidValues) {
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| 345 | selector.CopySelected = new BoolValue(true);
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| 346 | selector.NumberOfSelectedSubScopesParameter.Value = new IntValue(4);
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| 347 | selector.NumberOfSelectedSubScopesParameter.Hidden = true;
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| 348 | ParameterizeStochasticOperator(selector);
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| 349 | }
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| 350 | if (Problem != null) {
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| 351 | foreach (IXCSSelector selector in SelectorParameter.ValidValues.OfType<IXCSSelector>()) {
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| 352 | selector.NumerosityParameter.ActualName = Problem.Evaluator.NumerosityParameter.ActualName;
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| 353 | selector.NumerosityParameter.Hidden = true;
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| 354 | }
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| 355 | foreach (ISingleObjectiveSelector selector in SelectorParameter.ValidValues.OfType<ISingleObjectiveSelector>()) {
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| 356 | selector.MaximizationParameter.ActualName = Problem.MaximizationParameter.Name;
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| 357 | selector.MaximizationParameter.Hidden = true;
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| 358 | selector.QualityParameter.ActualName = Problem.Evaluator.FitnessParameter.ActualName;
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| 359 | selector.QualityParameter.Hidden = true;
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| 360 | }
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| 361 | }
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| 362 | }
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| 363 | private void ParameterizeManipulator() {
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| 364 | foreach (var op in Problem.Operators.OfType<IProbabilityMutatorOperator>()) {
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| 365 | op.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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| 366 | }
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| 367 | }
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| 368 | private void ParameterizeEvaluator(IXCSEvaluator evaluator) {
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| 369 | evaluator.ActualTimeParameter.ActualName = "Iteration";
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| 370 | evaluator.BetaParameter.ActualName = BetaParameter.Name;
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| 371 | evaluator.AlphaParameter.ActualName = AlphaParameter.Name;
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| 372 | evaluator.PowerParameter.ActualName = PowerParameter.Name;
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| 373 | evaluator.ErrorZeroParameter.ActualName = ErrorZeroParameter.Name;
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| 374 | }
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| 375 | private void ParameterizeStochasticOperator(IOperator op) {
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| 376 | IStochasticOperator stochasticOp = op as IStochasticOperator;
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| 377 | if (stochasticOp != null) {
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| 378 | stochasticOp.RandomParameter.ActualName = RandomCreator.RandomParameter.ActualName;
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| 379 | stochasticOp.RandomParameter.Hidden = true;
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| 380 | }
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| 381 | }
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| 382 |
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| 383 | private void UpdateSelectors() {
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| 384 | ISelector oldSelector = SelectorParameter.Value;
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| 385 | SelectorParameter.ValidValues.Clear();
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| 386 | ISelector defaultSelector = Problem.Operators.OfType<IXCSSelector>().FirstOrDefault();
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| 387 | if (defaultSelector == null) {
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| 388 | defaultSelector = Problem.Operators.OfType<ISelector>().FirstOrDefault();
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| 389 | }
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| 390 |
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| 391 | foreach (ISelector selector in Problem.Operators.OfType<ISelector>().OrderBy(x => x.Name))
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| 392 | SelectorParameter.ValidValues.Add(selector);
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| 393 |
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| 394 | if (oldSelector != null) {
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| 395 | ISelector selector = SelectorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldSelector.GetType());
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| 396 | if (selector != null) SelectorParameter.Value = selector;
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| 397 | else oldSelector = null;
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| 398 | }
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| 399 | if (oldSelector == null && defaultSelector != null)
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| 400 | SelectorParameter.Value = defaultSelector;
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| 401 | }
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| 402 |
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| 403 | private void UpdateCrossovers() {
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| 404 | ICrossover oldCrossover = CrossoverParameter.Value;
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| 405 | CrossoverParameter.ValidValues.Clear();
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|---|
| 406 | ICrossover defaultCrossover = Problem.Operators.OfType<ICrossover>().FirstOrDefault();
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| 407 |
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| 408 | foreach (ICrossover crossover in Problem.Operators.OfType<ICrossover>().OrderBy(x => x.Name))
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| 409 | CrossoverParameter.ValidValues.Add(crossover);
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|---|
| 410 |
|
|---|
| 411 | if (oldCrossover != null) {
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|---|
| 412 | ICrossover crossover = CrossoverParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldCrossover.GetType());
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|---|
| 413 | if (crossover != null) CrossoverParameter.Value = crossover;
|
|---|
| 414 | else oldCrossover = null;
|
|---|
| 415 | }
|
|---|
| 416 | if (oldCrossover == null && defaultCrossover != null)
|
|---|
| 417 | CrossoverParameter.Value = defaultCrossover;
|
|---|
| 418 | }
|
|---|
| 419 | private void UpdateMutators() {
|
|---|
| 420 | IManipulator oldMutator = MutatorParameter.Value;
|
|---|
| 421 | MutatorParameter.ValidValues.Clear();
|
|---|
| 422 | IManipulator defaultMutator = Problem.Operators.OfType<IManipulator>().FirstOrDefault();
|
|---|
| 423 |
|
|---|
| 424 | foreach (IManipulator mutator in Problem.Operators.OfType<IManipulator>().OrderBy(x => x.Name))
|
|---|
| 425 | MutatorParameter.ValidValues.Add(mutator);
|
|---|
| 426 | if (oldMutator != null) {
|
|---|
| 427 | IManipulator mutator = MutatorParameter.ValidValues.FirstOrDefault(x => x.GetType() == oldMutator.GetType());
|
|---|
| 428 | if (mutator != null) MutatorParameter.Value = mutator;
|
|---|
| 429 | else oldMutator = null;
|
|---|
| 430 | }
|
|---|
| 431 | if (oldMutator == null && defaultMutator != null)
|
|---|
| 432 | MutatorParameter.Value = defaultMutator;
|
|---|
| 433 | }
|
|---|
| 434 | private void UpdateAnalyzers() {
|
|---|
| 435 | Analyzer.Operators.Clear();
|
|---|
| 436 | FinalAnalyzer.Operators.Clear();
|
|---|
| 437 | if (Problem != null) {
|
|---|
| 438 | foreach (IAnalyzer analyzer in Problem.Operators.OfType<IAnalyzer>()) {
|
|---|
| 439 | Analyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
|
|---|
| 440 | FinalAnalyzer.Operators.Add(analyzer, analyzer.EnabledByDefault);
|
|---|
| 441 | }
|
|---|
| 442 | }
|
|---|
| 443 | }
|
|---|
| 444 |
|
|---|
| 445 | private LearningClassifierSystemMainLoop FindMainLoop(IOperator start) {
|
|---|
| 446 | IOperator mainLoop = start;
|
|---|
| 447 | while (mainLoop != null && !(mainLoop is LearningClassifierSystemMainLoop))
|
|---|
| 448 | mainLoop = ((SingleSuccessorOperator)mainLoop).Successor;
|
|---|
| 449 | if (mainLoop == null) return null;
|
|---|
| 450 | else return (LearningClassifierSystemMainLoop)mainLoop;
|
|---|
| 451 | }
|
|---|
| 452 | }
|
|---|
| 453 | }
|
|---|
