1 | package agents.ai2014.group12;
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2 |
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3 | import java.util.ArrayList;
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4 | import java.util.HashMap;
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5 | import java.util.List;
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6 | import java.util.Map;
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7 |
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8 | import genius.core.Bid;
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9 | import genius.core.issue.Value;
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10 | import genius.core.issue.ValueDiscrete;
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11 | import genius.core.utility.AbstractUtilitySpace;
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12 |
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13 | public class BidGenerator {
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14 | static ArrayList<Bid> bidCombinations;
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15 | static AbstractUtilitySpace utilitySpace;
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16 |
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17 | /**
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18 | * This function returns the best bid that an agent can make with regards to
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19 | * other agents.
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20 | *
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21 | * @param ut
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22 | * @param preference
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23 | * @param acceptingValue
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24 | * @param otherAgentsPreference
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25 | * @return
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26 | * @throws Exception
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27 | */
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28 |
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29 | public static Bid generateBid(AbstractUtilitySpace ut,
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30 | Preference preference, double acceptingValue,
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31 | HashMap<String, Preference> otherAgentsPreference) throws Exception {
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32 | System.out.println("Begin combinations");
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33 | utilitySpace = ut;
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34 | bidCombinations = new ArrayList<Bid>();
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35 |
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36 | if (acceptingValue == 0.9) {
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37 | return ut.getMaxUtilityBid();
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38 | }
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39 |
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40 | cartesianProductW(preference);
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41 |
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42 | ArrayList<Bid> filteredBidCombinations = filterCombos(acceptingValue,
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43 | 0.1);
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44 |
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45 | Bid returnBid = new Bid(ut.getDomain());
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46 | returnBid = getBestBid(filteredBidCombinations, ut, preference,
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47 | otherAgentsPreference);
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48 |
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49 | return returnBid;
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50 | }
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51 |
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52 | /**
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53 | * A wrapper function for the cartesianProduct of a agents preferences. Will
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54 | * make a List<List<Node>> data structured that will be used as input for
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55 | * cartesianProduct
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56 | *
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57 | * @param preference
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58 | * @throws Exception
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59 | */
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60 |
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61 | private static void cartesianProductW(Preference preference)
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62 | throws Exception {
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63 | List<List<Node>> blocks = new ArrayList<List<Node>>();
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64 |
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65 | for (int i = 0; i < preference.preferenceList.size(); i++) {
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66 | PreferenceBlock block = preference.preferenceList.get(i);
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67 | List<Node> nodes = new ArrayList<Node>();
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68 | for (int j = 0; j < block.nodeList.size(); j++) {
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69 | nodes.add(block.nodeList.get(j));
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70 | }
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71 | blocks.add(nodes);
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72 | }
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73 |
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74 | List<List<Node>> resultTest = cartesianProduct(blocks);
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75 | for (int i = 0; i < resultTest.size(); i++) {
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76 | List<Node> list = resultTest.get(i);
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77 | HashMap<Integer, Value> hsmp = new HashMap<Integer, Value>();
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78 | Bid bid = new Bid(utilitySpace.getDomain());
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79 | for (int j = 0; j < list.size(); j++) {
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80 | Node node = list.get(j);
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81 | ValueDiscrete val = new ValueDiscrete(node.getName());
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82 | Value value = (Value) val;
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83 | hsmp.put(j + 1, value);
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84 | bid = new Bid(utilitySpace.getDomain(), hsmp);
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85 | }
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86 | bidCombinations.add(bid);
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87 | }
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88 | }
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89 |
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90 | /**
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91 | * Will return a cartesianProduct list of the input list
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92 | *
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93 | * @param lists
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94 | * @return
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95 | */
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96 | protected static <T> List<List<T>> cartesianProduct(List<List<T>> lists) {
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97 | List<List<T>> resultLists = new ArrayList<List<T>>();
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98 | if (lists.size() == 0) {
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99 | resultLists.add(new ArrayList<T>());
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100 | return resultLists;
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101 | } else {
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102 | List<T> firstList = lists.get(0);
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103 | List<List<T>> remainingLists = cartesianProduct(lists.subList(1,
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104 | lists.size()));
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105 | for (T condition : firstList) {
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106 | for (List<T> remainingList : remainingLists) {
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107 | ArrayList<T> resultList = new ArrayList<T>();
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108 | resultList.add(condition);
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109 | resultList.addAll(remainingList);
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110 | resultLists.add(resultList);
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111 | }
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112 | }
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113 | }
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114 | return resultLists;
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115 | }
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116 |
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117 | /**
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118 | * Returns the best bid of the bid list, will calculate all the values of
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119 | * the bids and takes the best average bid for everybody and returns that
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120 | * Bid.
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121 | *
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122 | * @param bids
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123 | * @param ut
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124 | * @param preference
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125 | * @param otherAgentsPreference
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126 | * @return
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127 | * @throws Exception
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128 | */
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129 | private static Bid getBestBid(ArrayList<Bid> bids, AbstractUtilitySpace ut,
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130 | Preference preference,
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131 | HashMap<String, Preference> otherAgentsPreference) throws Exception {
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132 | ArrayList<ArrayList<Double>> list = new ArrayList<ArrayList<Double>>();
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133 | for (Bid bid : bids) {
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134 | ArrayList<Double> bidValues = new ArrayList<Double>();
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135 | for (Map.Entry<String, Preference> entry : otherAgentsPreference
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136 | .entrySet()) {
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137 | Preference p = (Preference) entry.getValue();
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138 | double bidValueP = p.getUtilityValue(bid);
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139 | bidValues.add(bidValueP);
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140 | }
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141 | }
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142 |
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143 | ArrayList<Double> averageValueOfBid = new ArrayList<Double>();
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144 | for (ArrayList<Double> listOfABid : list) {
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145 | double averageWeight = 0;
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146 | for (double bidListValues : listOfABid) {
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147 | averageWeight += bidListValues;
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148 | }
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149 | averageValueOfBid.add(averageWeight);
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150 | }
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151 |
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152 | int returnIndex = 0;
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153 | double biggest = 0;
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154 | for (int i = 0; i < averageValueOfBid.size(); i++) {
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155 | if (averageValueOfBid.get(i) > biggest) {
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156 | biggest = averageValueOfBid.get(i);
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157 | returnIndex = i;
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158 | }
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159 | }
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160 | return bids.get(returnIndex);
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161 | }
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162 |
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163 | /**
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164 | * Returns an filtered list of the bidcombinations. The filter is an range
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165 | * from the accepting value to a range percentage above the accepting value.
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166 | *
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167 | * @param acceptingValue
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168 | * @param range
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169 | * @return
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170 | * @throws Exception
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171 | */
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172 | public static ArrayList<Bid> filterCombos(double acceptingValue,
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173 | double range) throws Exception {
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174 | ArrayList<Bid> goodBidCombos = new ArrayList<Bid>();
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175 |
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176 | double minValue = acceptingValue;
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177 | double maxValue = acceptingValue + (acceptingValue * range);
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178 |
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179 | for (int i = 0; i < bidCombinations.size(); i++) {
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180 | Bid bid = bidCombinations.get(i);
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181 | double value = utilitySpace.getUtility(bid);
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182 | if (minValue < value && maxValue > value) {
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183 | goodBidCombos.add(bid);
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184 |
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185 | }
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186 | }
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187 |
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188 | if (goodBidCombos.size() != 0) {
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189 | return goodBidCombos;
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190 | } else
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191 | return filterCombos(acceptingValue, range * 1.5);
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192 |
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193 | }
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194 | }
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