1 | package agents.anac.y2018.yeela;
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2 |
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3 | import java.util.List;
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4 |
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5 | import java.util.HashMap;
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6 | import java.util.Random;
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7 |
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8 | import genius.core.Bid;
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9 | import genius.core.issue.Issue;
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10 | import genius.core.issue.IssueDiscrete;
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11 | import genius.core.issue.Value;
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12 | import genius.core.issue.ValueDiscrete;
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13 | import genius.core.parties.NegotiationInfo;
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14 | import genius.core.utility.AdditiveUtilitySpace;
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15 | import genius.core.utility.EvaluatorDiscrete;
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16 |
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17 | public class Individual implements Comparable<Individual> {
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18 | private Double ALPHA = 0.9; // TODO
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19 |
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20 | private HashMap<Integer, Value> m_gene;
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21 | private Double m_util;
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22 | private NegotiationInfo m_info;
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23 | private Random m_rand;
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24 | private Bid m_opponent;
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25 | private Double m_best;
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26 | private Double m_maxDist;
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27 |
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28 | public Individual(Bid b, NegotiationInfo info)
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29 | {
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30 | m_gene = b.getValues();
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31 | m_info = info;
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32 | m_util = CalcUtility();
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33 | m_rand = new Random();
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34 |
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35 | try
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36 | {
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37 | Bid best = m_info.getUtilitySpace().getMaxUtilityBid();
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38 | m_best = m_info.getUtilitySpace().getUtility(best);
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39 | m_maxDist = Dist(
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40 | best.getValues(),
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41 | m_info.getUtilitySpace().getMinUtilityBid().getValues());
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42 | }
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43 | catch (Exception e)
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44 | {
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45 | m_maxDist = Double.MIN_VALUE;
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46 | e.printStackTrace();
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47 | }
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48 | }
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49 |
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50 | @Override
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51 | public int compareTo(Individual other)
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52 | {
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53 | try
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54 | {
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55 | return (int) java.lang.Math.signum(this.GetFitness() - other.GetFitness());
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56 | }
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57 | catch (Exception e)
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58 | {
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59 | e.printStackTrace();
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60 | return 0;
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61 | }
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62 | }
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63 |
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64 | public Value GetValue(Integer key)
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65 | {
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66 | return m_gene.get(key);
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67 | }
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68 |
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69 | public void SetValue(Integer key, Value value)
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70 | {
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71 | m_gene.put(key, value);
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72 | }
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73 |
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74 | private Double TP()
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75 | {
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76 | // TODO
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77 | return 1.0;
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78 | }
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79 |
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80 | private Double Dist(HashMap<Integer, Value> v1, HashMap<Integer, Value> v2)
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81 | {
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82 | Double d = 0.0;
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83 |
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84 | AdditiveUtilitySpace additiveUtilitySpace = (AdditiveUtilitySpace) m_info.getUtilitySpace();
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85 | List<Issue> issues = additiveUtilitySpace.getDomain().getIssues();
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86 |
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87 | for (Issue issue : issues)
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88 | {
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89 | int issueNumber = issue.getNumber();
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90 | Double weight = additiveUtilitySpace.getWeight(issueNumber);
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91 |
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92 | // Assuming that issues are discrete only
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93 | EvaluatorDiscrete evaluatorDiscrete = (EvaluatorDiscrete) additiveUtilitySpace.getEvaluator(issueNumber);
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94 |
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95 | try
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96 | {
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97 | Double evaluation1 = evaluatorDiscrete.getEvaluation((ValueDiscrete)v1.get(issueNumber));
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98 | Double evaluation2 = evaluatorDiscrete.getEvaluation((ValueDiscrete)v2.get(issueNumber));
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99 |
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100 | d += (weight * Math.pow(evaluation1 - evaluation2, 2));
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101 | }
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102 | catch (Exception e)
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103 | {
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104 | d = Double.POSITIVE_INFINITY;
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105 | e.printStackTrace();
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106 | }
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107 | }
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108 |
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109 | return Math.sqrt(d);
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110 | }
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111 |
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112 | public void UpdateOpponent(Bid opponent)
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113 | {
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114 | m_opponent = opponent;
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115 | }
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116 |
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117 | public Double GetFitness()
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118 | {
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119 | Double otherSide = (1 - ALPHA) * TP() * (1 - (Dist(m_gene, m_opponent.getValues()) / m_maxDist));
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120 | Double ourSide = ALPHA * TP() * (this.GetUtility() / m_best);
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121 | return ourSide + otherSide;
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122 | }
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123 |
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124 | public Double GetUtility()
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125 | {
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126 | return m_util;
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127 | }
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128 |
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129 | private Double CalcUtility()
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130 | {
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131 | // TODO maybe simply call utilitySpace.getUtility(randomBid); see https://github.com/tdgunes/ExampleAgent/wiki/Generating-a-random-bid-with-a-utility-threshold
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132 | Double util = 0.0;
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133 |
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134 | AdditiveUtilitySpace additiveUtilitySpace = (AdditiveUtilitySpace) m_info.getUtilitySpace();
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135 | List<Issue> issues = additiveUtilitySpace.getDomain().getIssues();
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136 |
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137 | for (Issue issue : issues)
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138 | {
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139 | int issueNumber = issue.getNumber();
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140 | Double weight = additiveUtilitySpace.getWeight(issueNumber);
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141 |
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142 | // Assuming that issues are discrete only
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143 | IssueDiscrete issueDiscrete = (IssueDiscrete) issue;
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144 | EvaluatorDiscrete evaluatorDiscrete = (EvaluatorDiscrete) additiveUtilitySpace.getEvaluator(issueNumber);
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145 | Double evaluation = 0.0;
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146 |
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147 | for (ValueDiscrete valueDiscrete : issueDiscrete.getValues())
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148 | {
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149 | if (0 == valueDiscrete.getValue().compareTo(m_gene.get(issueNumber).toString()))
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150 | {
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151 | try
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152 | {
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153 | evaluation = evaluatorDiscrete.getEvaluation(valueDiscrete);
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154 | util += (weight * evaluation);
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155 | }
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156 | catch (Exception e)
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157 | {
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158 | e.printStackTrace();
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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 | return util;
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164 | }
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165 |
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166 | public Individual Clone()
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167 | {
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168 | Bid randomBid = m_info.getUtilitySpace().getDomain().getRandomBid(m_rand);
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169 |
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170 | try
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171 | {
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172 | for (Integer key : m_gene.keySet())
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173 | {
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174 | randomBid.putValue(key, m_gene.get(key));
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175 | }
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176 | }
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177 | catch (Exception e)
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178 | {
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179 | e.printStackTrace();
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180 | }
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181 |
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182 | Individual ind = new Individual(randomBid, m_info);
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183 | ind.UpdateOpponent(m_opponent);
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184 | return ind;
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185 | }
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186 |
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187 | public void Mutate()
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188 | {
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189 | try
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190 | {
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191 | AdditiveUtilitySpace additiveUtilitySpace = (AdditiveUtilitySpace) m_info.getUtilitySpace();
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192 | List<Issue> issues = additiveUtilitySpace.getDomain().getIssues();
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193 |
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194 | int randomNum = m_rand.nextInt(issues.size());
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195 | Issue issue = issues.get(randomNum);
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196 |
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197 | IssueDiscrete issueDiscrete = (IssueDiscrete) issue;
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198 | int issueNumber = issue.getNumber();
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199 | randomNum = issueNumber;
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200 | while (randomNum == issueNumber)
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201 | {
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202 | randomNum = m_rand.nextInt(issueDiscrete.getValues().size());
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203 | }
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204 |
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205 | Value newValue = issueDiscrete.getValues().get(randomNum);
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206 | m_gene.put(issueNumber, newValue);
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207 | }
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208 | catch (Exception e)
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209 | {
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210 | e.printStackTrace();
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211 | }
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212 |
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213 | }
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214 |
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215 | public void Crossover(Individual other)
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216 | {
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217 | try
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218 | {
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219 | AdditiveUtilitySpace additiveUtilitySpace = (AdditiveUtilitySpace) m_info.getUtilitySpace();
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220 | List<Issue> issues = additiveUtilitySpace.getDomain().getIssues();
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221 |
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222 | if (1 < issues.size()) // otherwise no need to crossover
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223 | {
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224 | int randomNum = m_rand.nextInt(issues.size() - 1) + 1; // minus one since crossover location is in gap between alleles
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225 |
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226 | for (Integer key : m_gene.keySet())
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227 | {
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228 | if (key > randomNum)
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229 | {
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230 | break;
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231 | }
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232 |
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233 | Value temp = m_gene.get(key);
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234 | m_gene.put(key, other.GetValue(key));
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235 | other.SetValue(key, temp);
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236 | }
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237 | }
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238 | }
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239 | catch (Exception e)
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240 | {
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241 | e.printStackTrace();
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242 | }
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243 | }
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244 | }
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