1 | package agents.anac.y2011.AgentK2;
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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.Random;
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7 |
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8 | import genius.core.Agent;
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9 | import genius.core.Bid;
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10 | import genius.core.actions.Accept;
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11 | import genius.core.actions.Action;
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12 | import genius.core.actions.ActionWithBid;
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13 | import genius.core.actions.Offer;
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14 | import genius.core.issue.Issue;
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15 | import genius.core.issue.IssueDiscrete;
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16 | import genius.core.issue.IssueInteger;
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17 | import genius.core.issue.IssueReal;
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18 | import genius.core.issue.Value;
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19 | import genius.core.issue.ValueInteger;
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20 | import genius.core.issue.ValueReal;
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21 |
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22 | public class Agent_K2 extends Agent {
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23 |
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24 | private Action partner = null;
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25 | private HashMap<Bid, Double> offeredBidMap;
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26 | private double target;
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27 | private double bidTarget;
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28 | private double sum;
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29 | private double sum2;
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30 | private int rounds;
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31 | private double tremor;
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32 | private final boolean TEST_EQUIVALENCE = false;
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33 | private Random random100;
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34 | private Random random200;
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35 | private Random random300;
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36 | private Random random400;
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37 |
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38 | @Override
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39 | public void init() {
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40 | offeredBidMap = new HashMap<Bid, Double>();
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41 | target = 1.0;
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42 | bidTarget = 1.0;
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43 | sum = 0.0;
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44 | sum2 = 0.0;
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45 | rounds = 0;
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46 | tremor = 2.0;
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47 |
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48 | if (TEST_EQUIVALENCE) {
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49 | random100 = new Random(100);
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50 | random200 = new Random(200);
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51 | random300 = new Random(300);
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52 | random400 = new Random(400);
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53 | } else {
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54 | random100 = new Random();
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55 | random200 = new Random();
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56 | random300 = new Random();
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57 | random400 = new Random();
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58 | }
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59 | }
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60 |
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61 | @Override
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62 | public String getName() {
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63 | return "Agent_K2";
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64 | }
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65 |
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66 | @Override
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67 | public String getVersion() {
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68 | return "0.31415_discountFix";
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69 | }
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70 |
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71 | @Override
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72 | public void ReceiveMessage(Action opponentAction) {
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73 | partner = opponentAction;
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74 | }
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75 |
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76 | @Override
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77 | public Action chooseAction() {
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78 | Action action = null;
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79 | try {
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80 | if (partner == null) {
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81 | action = selectBid();
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82 | }
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83 | if (partner instanceof Offer) {
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84 | Bid offeredBid = ((Offer) partner).getBid();
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85 |
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86 | double p = acceptProbability(offeredBid);
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87 |
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88 | if (p > random100.nextDouble()) {
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89 | action = new Accept(getAgentID(), offeredBid);
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90 | } else {
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91 | action = selectBid();
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92 | }
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93 | }
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94 | } catch (Exception e) {
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95 | e.printStackTrace();
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96 | action = new Accept(getAgentID(),
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97 | ((ActionWithBid) partner).getBid());
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98 | }
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99 | return action;
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100 | }
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101 |
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102 | private Action selectBid() {
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103 | Bid nextBid = null;
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104 |
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105 | ArrayList<Bid> bidTemp = new ArrayList<Bid>();
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106 |
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107 | for (Bid bid : offeredBidMap.keySet()) {
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108 | if (offeredBidMap.get(bid) > target) {
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109 | bidTemp.add(bid);
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110 | }
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111 | }
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112 |
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113 | int size = bidTemp.size();
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114 | if (size > 0) {
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115 | int sindex = (int) Math.floor(random200.nextDouble() * size);
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116 | nextBid = bidTemp.get(sindex);
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117 | } else {
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118 | double searchUtil = 0.0;
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119 | try {
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120 | int loop = 0;
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121 | while (searchUtil < bidTarget) {
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122 | if (loop > 500) {
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123 | bidTarget -= 0.01;
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124 | loop = 0;
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125 | }
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126 | nextBid = searchBid();
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127 | searchUtil = utilitySpace.getUtility(nextBid);
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128 | loop++;
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129 | }
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130 | } catch (Exception e) {
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131 | e.printStackTrace();
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132 | }
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133 | }
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134 |
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135 | if (nextBid == null) {
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136 | return (new Accept(getAgentID(),
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137 | ((ActionWithBid) partner).getBid()));
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138 | }
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139 | return (new Offer(getAgentID(), nextBid));
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140 | }
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141 |
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142 | private Bid searchBid() throws Exception {
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143 | HashMap<Integer, Value> values = new HashMap<Integer, Value>();
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144 | List<Issue> issues = utilitySpace.getDomain().getIssues();
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145 |
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146 | Bid bid = null;
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147 |
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148 | for (Issue lIssue : issues) {
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149 | switch (lIssue.getType()) {
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150 | case DISCRETE:
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151 | IssueDiscrete lIssueDiscrete = (IssueDiscrete) lIssue;
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152 | int optionIndex = random300
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153 | .nextInt(lIssueDiscrete.getNumberOfValues());
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154 | values.put(lIssue.getNumber(),
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155 | lIssueDiscrete.getValue(optionIndex));
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156 | break;
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157 | case REAL:
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158 | IssueReal lIssueReal = (IssueReal) lIssue;
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159 | int optionInd = random300.nextInt(
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160 | lIssueReal.getNumberOfDiscretizationSteps() - 1);
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161 | values.put(lIssueReal.getNumber(),
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162 | new ValueReal(lIssueReal.getLowerBound() + (lIssueReal
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163 | .getUpperBound() - lIssueReal.getLowerBound())
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164 | * (optionInd) / (lIssueReal
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165 | .getNumberOfDiscretizationSteps())));
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166 | break;
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167 | case INTEGER:
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168 | IssueInteger lIssueInteger = (IssueInteger) lIssue;
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169 | int optionIndex2 = lIssueInteger.getLowerBound()
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170 | + random300.nextInt(lIssueInteger.getUpperBound()
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171 | - lIssueInteger.getLowerBound());
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172 | values.put(lIssueInteger.getNumber(),
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173 | new ValueInteger(optionIndex2));
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174 | break;
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175 | default:
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176 | throw new Exception("issue type " + lIssue.getType()
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177 | + " not supported by SimpleAgent2");
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178 | }
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179 | }
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180 |
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181 | bid = new Bid(utilitySpace.getDomain(), values);
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182 | return bid;
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183 | }
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184 |
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185 | double acceptProbability(Bid offeredBid) throws Exception {
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186 |
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187 | double offeredUtility = utilitySpace.getUtility(offeredBid);
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188 | offeredBidMap.put(offeredBid, offeredUtility);
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189 |
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190 | sum += offeredUtility;
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191 | sum2 += offeredUtility * offeredUtility;
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192 | rounds++;
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193 |
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194 | double mean = sum / rounds;
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195 |
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196 | double variance = (sum2 / rounds) - (mean * mean);
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197 |
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198 | double deviation = Math.sqrt(variance * 12);
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199 | if (Double.isNaN(deviation)) {
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200 | deviation = 0.0;
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201 | }
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202 |
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203 | double time = timeline.getTime();
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204 |
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205 | double t = time * time * time;
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206 |
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207 | if (offeredUtility < 0 || offeredUtility > 1.05) {
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208 | throw new Exception("utility " + offeredUtility + " outside [0,1]");
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209 | }
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210 |
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211 | if (t < 0 || t > 1) {
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212 | throw new Exception("time " + t + " outside [0,1]");
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213 | }
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214 |
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215 | if (offeredUtility > 1.) {
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216 | offeredUtility = 1;
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217 | }
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218 |
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219 | double estimateMax = mean + ((1 - mean) * deviation);
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220 |
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221 | double alpha = 1 + tremor + (10 * mean) - (2 * tremor * mean);
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222 | double beta = alpha + (random400.nextDouble() * tremor) - (tremor / 2);
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223 |
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224 | double preTarget = 1 - (Math.pow(time, alpha) * (1 - estimateMax));
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225 | double preTarget2 = 1 - (Math.pow(time, beta) * (1 - estimateMax));
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226 |
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227 | double ratio = (deviation + 0.1) / (1 - preTarget);
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228 | if (Double.isNaN(ratio) || ratio > 2.0) {
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229 | ratio = 2.0;
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230 | }
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231 |
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232 | double ratio2 = (deviation + 0.1) / (1 - preTarget2);
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233 | if (Double.isNaN(ratio2) || ratio2 > 2.0) {
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234 | ratio2 = 2.0;
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235 | }
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236 |
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237 | target = ratio * preTarget + 1 - ratio;
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238 | bidTarget = ratio2 * preTarget2 + 1 - ratio2;
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239 |
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240 | double m = t * (-300) + 400;
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241 | if (target > estimateMax) {
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242 | double r = target - estimateMax;
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243 | double f = 1 / (r * r);
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244 | if (f > m || Double.isNaN(f))
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245 | f = m;
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246 | double app = r * f / m;
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247 | target = target - app;
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248 | } else {
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249 | target = estimateMax;
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250 | }
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251 |
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252 | if (bidTarget > estimateMax) {
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253 | double r = bidTarget - estimateMax;
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254 | double f = 1 / (r * r);
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255 | if (f > m || Double.isNaN(f))
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256 | f = m;
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257 | double app = r * f / m;
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258 | bidTarget = bidTarget - app;
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259 | } else {
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260 | bidTarget = estimateMax;
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261 | }
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262 |
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263 | // test code for Discount Factor
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264 | double discount_utility = utilitySpace
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265 | .getUtilityWithDiscount(offeredBid, time);
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266 |
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267 | double discount_ratio = discount_utility / offeredUtility;
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268 | if (!Double.isNaN(discount_utility) && !Double.isNaN(discount_ratio)) {
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269 | target *= discount_ratio;
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270 | bidTarget *= discount_ratio;
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271 | }
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272 |
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273 | double utilityEvaluation = offeredUtility - estimateMax;
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274 | double satisfy = offeredUtility - target;
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275 |
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276 | double p = (Math.pow(time, alpha) / 5) + utilityEvaluation + satisfy;
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277 | if (p < 0.1) {
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278 | p = 0.0;
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279 | }
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280 |
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281 | return p;
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282 | }
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283 |
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284 | @Override
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285 | public String getDescription() {
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286 | return "ANAC2011 compatible with non-linear utility spaces";
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287 | }
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288 | }
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