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.Algorithms.MonteCarloTreeSearch.Base;
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5 | using HeuristicLab.Problems.GrammaticalOptimization;
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6 |
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7 | namespace HeuristicLab.Algorithms.MonteCarloTreeSearch.Simulation
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8 | {
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9 | public class RandomSimulation : ISimulation
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10 | {
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11 | private IProblem problem;
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12 | private IGrammar grammar;
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13 | private Random random;
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14 | private int maxLen;
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15 |
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16 | public RandomSimulation(IProblem problem, Random random, int maxLen)
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17 | {
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18 | this.problem = problem;
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19 | this.grammar = problem.Grammar;
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20 | this.random = random;
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21 | this.maxLen = maxLen;
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22 | }
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23 |
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24 | public double Simulate(TreeNode node, out string simulatedPhrase)
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25 | {
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26 | Sequence sequence = new Sequence(node.phrase);
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27 | List<int> ntPositions = new List<int>();
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28 | while (!sequence.IsTerminal)
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29 | {
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30 | // select one random nt-symbol
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31 | ntPositions.Clear();
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32 | for (int i = 0; i < sequence.Length; i++)
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33 | {
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34 | if (grammar.IsNonTerminal(sequence[i]))
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35 | {
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36 | ntPositions.Add(i);
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37 | }
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38 | }
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39 | int ntSymbolIndex = ntPositions[random.Next(ntPositions.Count)];
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40 | char ntSymbol = sequence[ntSymbolIndex];
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41 |
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42 | // select one random alternative for nt-symbol
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43 | IEnumerable<Sequence> alternatives = grammar.GetAlternatives(ntSymbol);
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44 | Sequence alternative = alternatives.ElementAt(random.Next(alternatives.Count()));
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45 | if (sequence.Length + alternative.Length - 1 <= maxLen)
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46 | {
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47 | sequence.ReplaceAt(ntSymbolIndex, 1, alternative);
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48 | }
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49 | }
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50 | simulatedPhrase = sequence.ToString();
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51 | return problem.Evaluate(sequence.ToString());
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52 | }
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53 | }
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54 | }
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