[9565] | 1 | using System;
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| 2 | using System.Collections.Generic;
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| 3 | using System.Linq;
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| 4 | using HeuristicLab.Common;
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| 5 | using HeuristicLab.Core;
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| 6 | using HeuristicLab.Data;
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| 7 | using HeuristicLab.Parameters;
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| 8 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 9 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 10 |
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| 11 | namespace HeuristicLab.Problems.Robocode
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| 12 | {
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| 13 | /// <summary>
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| 14 | /// Takes two parent individuals P0 and P1 each. Selects a random node N0 of P0 and a random node N1 of P1.
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| 15 | /// And replaces the branch with root0 N0 in P0 with N1 from P1 if the tree-size limits are not violated.
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| 16 | /// When recombination with N0 and N1 would create a tree that is too large or invalid the operator randomly selects new N0 and N1
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| 17 | /// until a valid configuration is found.
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| 18 | /// </summary>
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| 19 | [Item("RobocodeMethodCrossover", "An operator which performs crossover of randomly chosen statements with a method.")]
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| 20 | [StorableClass]
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| 21 | public class RobocodeMethodCrossover : SymbolicExpressionTreeCrossover//, ISymbolicExpressionTreeSizeConstraintOperator
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| 22 | {
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| 23 |
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| 24 | #region Parameter Names
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| 25 |
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| 26 | private const string HomologousCrossoverPrameterName = "HomologousCrossover";
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| 27 | private const string MaximumCrossoverMethodsParameterName = "MaximumCrossoverMethods";
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| 28 |
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| 29 | #endregion
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| 30 |
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| 31 | #region Parameter Properties
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| 32 |
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| 33 | public IValueLookupParameter<BoolValue> HomologousCrossoverParameter
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| 34 | {
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| 35 | get { return (IValueLookupParameter<BoolValue>)Parameters[HomologousCrossoverPrameterName]; }
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| 36 | }
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| 37 |
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| 38 | public IValueLookupParameter<IntValue> MaximumCrossoverMethodsParameter
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| 39 | {
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| 40 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumCrossoverMethodsParameterName]; }
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| 41 | }
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| 42 | #endregion
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| 43 |
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| 44 | #region Properties
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| 45 |
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| 46 | public BoolValue HomologousCrossover
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| 47 | {
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| 48 | get { return HomologousCrossoverParameter.ActualValue; }
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| 49 | }
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| 50 |
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| 51 | public IntValue MaximumCrossoverMethods
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| 52 | {
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| 53 | get { return MaximumCrossoverMethodsParameter.ActualValue; }
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| 54 | }
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| 55 |
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| 56 | #endregion
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| 57 |
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| 58 | [StorableConstructor]
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| 59 | protected RobocodeMethodCrossover(bool deserializing) : base(deserializing) { }
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| 60 | protected RobocodeMethodCrossover(RobocodeMethodCrossover original, Cloner cloner) :
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| 61 | base(original, cloner) { }
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| 62 | public RobocodeMethodCrossover()
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| 63 | : base()
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| 64 | {
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| 65 | Parameters.Add(new ValueLookupParameter<BoolValue>(HomologousCrossoverPrameterName,
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| 66 | "Specifies if the number of statements exchanged between the two parents is the same.", new BoolValue(false)));
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| 67 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumCrossoverMethodsParameterName,
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| 68 | "The maximal methods to apply crossover on (0 or a number higher than the count of " +
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| 69 | "methods means applying crossover to them all).", new IntValue(0)));
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| 70 | }
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| 71 |
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| 72 | public override IDeepCloneable Clone(Cloner cloner)
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| 73 | {
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| 74 | return new RobocodeMethodCrossover(this, cloner);
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| 75 | }
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| 76 |
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| 77 | public override ISymbolicExpressionTree Crossover(IRandom random,
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| 78 | ISymbolicExpressionTree parent0, ISymbolicExpressionTree parent1)
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| 79 | {
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| 80 | return Cross(random, parent0, parent1, HomologousCrossover.Value,
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| 81 | MaximumCrossoverMethods.Value);
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| 82 | }
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| 83 |
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| 84 | public static ISymbolicExpressionTree Cross(IRandom random,
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| 85 | ISymbolicExpressionTree parent0, ISymbolicExpressionTree parent1,
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| 86 | bool homologous, int maximumCrossoverMethods)
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| 87 | {
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| 88 | // select a random crossover point in the first parent
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| 89 | List<CutPoint> crossoverPoints0;
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| 90 | SelectCrossoverPoint(random, parent0, maximumCrossoverMethods, out crossoverPoints0);
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| 91 |
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| 92 | foreach (CutPoint c in crossoverPoints0)
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| 93 | {
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| 94 | List<ISymbolicExpressionTreeNode> allowedBranches = new List<ISymbolicExpressionTreeNode>();
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| 95 | parent1.Root.ForEachNodePostfix((n) =>
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| 96 | {
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| 97 | if (n.Symbol.GetType() == c.Child.Symbol.GetType())
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| 98 | allowedBranches.Add(n);
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| 99 | });
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| 100 |
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| 101 | if (allowedBranches.Count == 0)
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| 102 | {
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| 103 | break;
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| 104 | }
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| 105 | else
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| 106 | {
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| 107 | ISymbolicExpressionTreeNode branch = allowedBranches.FirstOrDefault();
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| 108 | int startBranchParent0 = (c.Child.SubtreeCount <= 2)? 0 : random.Next(0, c.Child.SubtreeCount - 2);
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| 109 | int endBranchParent0 = (c.Child.SubtreeCount <= 2) ? 1 : random.Next(startBranchParent0 + 1, c.Child.SubtreeCount - 1);
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| 110 | int Parent0Branches = endBranchParent0 - startBranchParent0;
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| 111 |
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| 112 | for (int i = 0; i < Parent0Branches; i++)
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| 113 | {
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| 114 | c.Child.RemoveSubtree(startBranchParent0);
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| 115 | }
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| 116 |
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| 117 | if (homologous)
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| 118 | {
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| 119 | for (int j = startBranchParent0; j <= endBranchParent0; j++)
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| 120 | {
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| 121 | c.Child.AddSubtree(branch.GetSubtree(j));
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| 122 | }
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| 123 | }
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| 124 | else
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| 125 | {
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| 126 | int startBranchParent1 = (branch.SubtreeCount <= 2) ? 0 : random.Next(0, branch.SubtreeCount - 2);
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| 127 | int endBranchParent1 = (branch.SubtreeCount <= 2) ? 1 : random.Next(startBranchParent1 + 1, branch.SubtreeCount - 1);
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| 128 | int Parent1Branches = endBranchParent1 - startBranchParent1;
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| 129 |
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| 130 | for (int j = startBranchParent1; j <= endBranchParent1 && c.Child.SubtreeCount < c.Child.Symbol.MaximumArity; j++)
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| 131 | {
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| 132 | c.Child.AddSubtree(branch.GetSubtree(j));
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| 133 | }
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| 134 | }
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| 135 | }
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| 136 | }
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| 137 |
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| 138 | return parent0;
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| 139 | }
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| 140 |
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| 141 | private static void SelectCrossoverPoint(IRandom random, ISymbolicExpressionTree parent0,
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| 142 | int maximumCrossoverMethods, out List<CutPoint> crossoverPoints)
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| 143 | {
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| 144 | List<CutPoint> MethodPoints = new List<CutPoint>();
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| 145 | parent0.Root.ForEachNodePostfix((n) =>
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| 146 | {
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| 147 | if (n.SubtreeCount > 0 && n != parent0.Root)
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| 148 | {
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| 149 | foreach (var child in n.Subtrees)
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| 150 | {
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| 151 | if (child.Symbol is Run ||
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| 152 | child.Symbol is OnBulletHit ||
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| 153 | child.Symbol is OnBulletMissed ||
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| 154 | child.Symbol is OnHitByBullet ||
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| 155 | child.Symbol is OnHitRobot ||
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| 156 | child.Symbol is OnHitWall ||
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| 157 | child.Symbol is OnScannedRobot)
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| 158 | MethodPoints.Add(new CutPoint(n, child));
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| 159 | }
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| 160 | }
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| 161 | });
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| 162 |
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| 163 | if (maximumCrossoverMethods == 0)
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| 164 | crossoverPoints = MethodPoints;
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| 165 | else
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| 166 | {
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| 167 | crossoverPoints = new List<CutPoint>();
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| 168 | for (int i = 0; i < maximumCrossoverMethods; i++)
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| 169 | {
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| 170 | CutPoint c = MethodPoints.SelectRandom(random);
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| 171 | crossoverPoints.Add(c);
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| 172 | MethodPoints.Remove(c);
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| 173 | if (MethodPoints.Count == 0) break;
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| 174 | }
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| 175 | }
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| 176 | }
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| 177 |
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| 178 | /*private static ISymbolicExpressionTreeNode SelectRandomBranch(IRandom random, IEnumerable<ISymbolicExpressionTreeNode> branches, double internalNodeProbability)
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| 179 | {
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| 180 | if (internalNodeProbability < 0.0 || internalNodeProbability > 1.0) throw new ArgumentException("internalNodeProbability");
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| 181 | List<ISymbolicExpressionTreeNode> allowedInternalBranches;
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| 182 | List<ISymbolicExpressionTreeNode> allowedLeafBranches;
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| 183 | if (random.NextDouble() < internalNodeProbability)
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| 184 | {
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| 185 | // select internal node if possible
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| 186 | allowedInternalBranches = (from branch in branches
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| 187 | where branch != null && branch.SubtreeCount > 0
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| 188 | select branch).ToList();
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| 189 | if (allowedInternalBranches.Count > 0)
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| 190 | {
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| 191 | return allowedInternalBranches.SelectRandom(random);
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| 192 | }
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| 193 | else
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| 194 | {
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| 195 | // no internal nodes allowed => select leaf nodes
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| 196 | allowedLeafBranches = (from branch in branches
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| 197 | where branch == null || branch.SubtreeCount == 0
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| 198 | select branch).ToList();
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| 199 | return allowedLeafBranches.SelectRandom(random);
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| 200 | }
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| 201 | }
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| 202 | else
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| 203 | {
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| 204 | // select leaf node if possible
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| 205 | allowedLeafBranches = (from branch in branches
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| 206 | where branch == null || branch.SubtreeCount == 0
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| 207 | select branch).ToList();
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| 208 | if (allowedLeafBranches.Count > 0)
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| 209 | {
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| 210 | return allowedLeafBranches.SelectRandom(random);
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| 211 | }
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| 212 | else
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| 213 | {
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| 214 | allowedInternalBranches = (from branch in branches
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| 215 | where branch != null && branch.SubtreeCount > 0
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| 216 | select branch).ToList();
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| 217 | return allowedInternalBranches.SelectRandom(random);
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| 218 | }
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| 219 | }
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| 220 | }*/
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| 221 | }
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| 222 | }
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