1 | package negotiator.boaframework.opponentmodel;
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2 |
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3 | import java.util.HashMap;
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4 | import java.util.List;
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5 | import java.util.Map;
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6 |
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7 | import genius.core.Bid;
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8 | import genius.core.boaframework.NegotiationSession;
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9 | import genius.core.boaframework.OpponentModel;
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10 | import genius.core.issue.Issue;
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11 | import genius.core.issue.Value;
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12 | import genius.core.utility.AdditiveUtilitySpace;
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13 | import negotiator.boaframework.opponentmodel.agentlg.BidStatistic;
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14 | import negotiator.boaframework.opponentmodel.tools.UtilitySpaceAdapter;
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15 |
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16 | /**
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17 | * Adaptation of the opponent model used by AgentLG in the ANAC2012 to be
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18 | * compatible with the BOA framework.
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19 | *
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20 | * Note that originally, the model sums up all value scores which entails that
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21 | * the total preference of a bid can be as high as offered bids * issues. The
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22 | * value score was equal to the amount of times the value was offered divided by
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23 | * total amount of bids offered by the opponent.
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24 | *
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25 | * In my implementation I normalize each value score by the highest value,
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26 | * similar to the implementation of preference profiles in Genius. Finally I sum
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27 | * all results and divide by the amount of issues. This is identical to assuming
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28 | * that the issue weights are uniform.
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29 | *
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30 | * Tim Baarslag, Koen Hindriks, Mark Hendrikx, Alex Dirkzwager and Catholijn M.
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31 | * Jonker. Decoupling Negotiating Agents to Explore the Space of Negotiation
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32 | * Strategies
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33 | *
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34 | * @author Mark Hendrikx
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35 | */
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36 | public class AgentLGModel extends OpponentModel {
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37 |
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38 | /**
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39 | * Creates objects to keep track of how many times each value has been
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40 | * offered for an issue
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41 | */
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42 | private HashMap<Issue, BidStatistic> statistic = new HashMap<Issue, BidStatistic>();
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43 | /** Cache the issues of the domain for performanc reasons */
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44 | private List<Issue> issues;
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45 |
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46 | /**
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47 | * Initialize the opponent model by creating an object to keep track of the
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48 | * values for each issue.
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49 | */
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50 | @Override
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51 | public void init(NegotiationSession negotiationSession, Map<String, Double> parameters) {
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52 | this.negotiationSession = negotiationSession;
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53 | issues = negotiationSession.getUtilitySpace().getDomain().getIssues();
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54 | for (Issue issue : issues) {
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55 | statistic.put(issue, new BidStatistic(issue));
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56 | }
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57 | }
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58 |
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59 | /**
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60 | * Update the opponent model by updating the value score for each issue.
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61 | *
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62 | * @param opponentBid
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63 | * @param time
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64 | * of offering
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65 | */
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66 | @Override
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67 | public void updateModel(Bid opponentBid, double time) {
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68 | try {
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69 | // updates statistics
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70 | for (Issue issue : statistic.keySet()) {
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71 | Value v = opponentBid.getValue(issue.getNumber());
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72 | statistic.get(issue).add(v);
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73 | }
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74 | } catch (Exception e) {
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75 | e.printStackTrace();
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76 | }
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77 | }
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78 |
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79 | /**
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80 | * @return utility of the opponent's bid
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81 | */
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82 | public double getBidEvaluation(Bid bid) {
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83 | double ret = 0;
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84 | for (Issue issue : issues) {
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85 | try {
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86 | ret += statistic.get(issue).getValueUtility(bid.getValue(issue.getNumber()));
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87 | } catch (Exception e) {
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88 | e.printStackTrace();
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89 | }
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90 | }
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91 | return (ret / issues.size());
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92 | }
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93 |
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94 | /**
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95 | * @return the uniform issue weight
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96 | */
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97 | public double getWeight(Issue issue) {
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98 | return (1.0 / issues.size());
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99 | }
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100 |
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101 | /**
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102 | * @return utilityspace created by using the opponent model adapter.
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103 | */
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104 | @Override
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105 | public AdditiveUtilitySpace getOpponentUtilitySpace() {
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106 | return new UtilitySpaceAdapter(this, negotiationSession.getUtilitySpace().getDomain());
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107 | }
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108 |
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109 | public void cleanUp() {
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110 | super.cleanUp();
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111 | }
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112 |
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113 | @Override
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114 | public String getName() {
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115 | return "AgentLG Model";
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116 | }
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117 | } |
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