1 | using System.Diagnostics;
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2 | using HeuristicLab.Algorithms.Bandits;
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3 | using HeuristicLab.Algorithms.MonteCarloTreeSearch.Base;
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4 | using HeuristicLab.Algorithms.MonteCarloTreeSearch.Simulation;
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5 | using HeuristicLab.Problems.GrammaticalOptimization;
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6 | using System;
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7 | using System.Linq;
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8 | using System.Threading;
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9 |
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10 | namespace HeuristicLab.Algorithms.MonteCarloTreeSearch
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11 | {
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12 | public class MonteCarloTreeSearch_PruneLeaves : MonteCarloTreeSearch
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13 | {
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14 | public MonteCarloTreeSearch_PruneLeaves(ISymbolicExpressionTreeProblem problem, int maxLen, Random random, IBanditPolicy behaviourPolicy,
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15 | ISimulation simulationPolicy)
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16 | : base(problem, maxLen, random, behaviourPolicy, simulationPolicy)
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17 | {
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18 | }
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19 |
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20 | public override void Run(int maxIterations)
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21 | {
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22 | Reset();
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23 | int selections = 0;
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24 | TreeNode currentNode;
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25 | string phrase;
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26 | string simulatedPhrase;
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27 | double quality;
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28 | for (int i = 0; !StopRequested && i < maxIterations; i++)
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29 | {
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30 | currentNode = rootNode;
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31 |
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32 | while (!currentNode.IsLeaf())
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33 | {
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34 | int currentActionIndex = behaviourPolicy.SelectAction(random,
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35 | currentNode.GetChildActionInfos());
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36 | currentNode = currentNode.children[currentActionIndex];
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37 | selections++;
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38 | CheckSelection(currentNode, selections);
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39 | }
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40 |
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41 | phrase = currentNode.phrase;
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42 |
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43 | if (phrase.Length <= maxLen)
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44 | {
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45 | // Version 2:
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46 | if (currentNode.children != null && !currentNode.children.Any())
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47 | {
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48 | // already removed all child nodes so remove it too..
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49 | currentNode.parent.RemoveChildren(currentNode);
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50 | i--;
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51 | continue;
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52 | }
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53 | ExpandTreeNode(currentNode);
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54 | if (currentNode.children.Any())
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55 | {
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56 | currentNode =
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57 | currentNode.children[behaviourPolicy.SelectAction(random, currentNode.GetChildActionInfos())
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58 | ];
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59 | selections++;
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60 | CheckSelection(currentNode, selections);
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61 | }
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62 | else
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63 | {
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64 | // Version 2:
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65 | // remove currentNode from tree..
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66 | currentNode.parent.RemoveChildren(currentNode);
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67 | }
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68 | }
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69 | if (currentNode.phrase.Length <= maxLen)
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70 | {
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71 | quality = simulation.Simulate(currentNode, out simulatedPhrase);
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72 | OnSolutionEvaluated(simulatedPhrase, quality);
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73 |
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74 | OnIterationFinishedChanged(goodSelections, selections);
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75 |
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76 | Propagate(currentNode, quality);
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77 | }
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78 | else
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79 | {
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80 | i--;
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81 |
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82 | }
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83 | }
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84 | }
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85 | }
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86 | }
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