| 1 | package agents.anac.y2012.MetaAgent;
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| 2 |
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| 3 | import java.util.ArrayList;
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| 4 | import java.util.Iterator;
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| 5 | import java.util.List;
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| 6 | import java.util.Map.Entry;
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| 7 |
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| 8 | import agents.anac.y2010.AgentSmith.AgentSmith;
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| 9 | import agents.anac.y2011.AgentK2.Agent_K2;
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| 10 | import agents.anac.y2011.BramAgent.BRAMAgent;
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| 11 | import agents.anac.y2011.Gahboninho.Gahboninho;
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| 12 | import agents.anac.y2011.HardHeaded.KLH;
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| 13 | import agents.anac.y2011.TheNegotiator.TheNegotiator;
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| 14 | import agents.anac.y2011.ValueModelAgent.ValueModelAgent;
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| 15 | import agents.anac.y2012.MetaAgent.agents.Chameleon.Chameleon;
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| 16 | import agents.anac.y2012.MetaAgent.agents.DNAgent.DNAgent;
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| 17 | import agents.anac.y2012.MetaAgent.agents.GYRL.GYRL;
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| 18 | import agents.anac.y2012.MetaAgent.agents.LYY.LYYAgent;
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| 19 | import agents.anac.y2012.MetaAgent.agents.MrFriendly.MrFriendly;
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| 20 | import agents.anac.y2012.MetaAgent.agents.ShAgent.ShAgent;
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| 21 | import agents.anac.y2012.MetaAgent.agents.SimpleAgentNew.SimpleAgentNew;
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| 22 | import agents.anac.y2012.MetaAgent.agents.WinnerAgent.WinnerAgent2;
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| 23 | import genius.core.Agent;
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| 24 | import genius.core.Domain;
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| 25 | import genius.core.SupportedNegotiationSetting;
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| 26 | import genius.core.actions.Action;
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| 27 | import genius.core.actions.EndNegotiation;
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| 28 | import genius.core.actions.Offer;
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| 29 | import genius.core.issue.Issue;
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| 30 | import genius.core.issue.Objective;
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| 31 | import genius.core.issue.ValueDiscrete;
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| 32 | import genius.core.utility.AdditiveUtilitySpace;
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| 33 | import genius.core.utility.EVALUATORTYPE;
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| 34 | import genius.core.utility.Evaluator;
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| 35 | import genius.core.utility.EvaluatorDiscrete;
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| 36 | import genius.core.utility.EvaluatorInteger;
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| 37 | import genius.core.utility.EvaluatorReal;
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| 38 |
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| 39 | public class MetaAgent extends Agent {
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| 40 | private Agent myAgent;
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| 41 | private String myAgentName;
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| 42 | private boolean agentInit;
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| 43 | private Action actionOfPartner;
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| 44 | private boolean first;
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| 45 | double[] params;
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| 46 | double opponentFirstBid;
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| 47 |
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| 48 | @Override
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| 49 | public void init() {
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| 50 | agentInit = false;
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| 51 | first = false;
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| 52 | opponentFirstBid = 0;
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| 53 | Domain d = this.utilitySpace.getDomain();
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| 54 | myAgentName = "";
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| 55 | }
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| 56 |
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| 57 | private String[][] getRegression() {
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| 58 | String[][] reg = new String[18][12];
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| 59 | reg[0] = "IAMcrazyhaggler,0.077,0,0.137,0.000000000,0.015,0,0,0,1.311,-0.03,0.556"
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| 60 | .split(",");
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| 61 | reg[1] = "LYYAgent,-1.22,-0.016,0.23,0.000000000,0.027,0.026,1.042,1.372,1.482,0,0.572"
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| 62 | .split(",");
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| 63 | reg[2] = "Chameleon,-2.185,-0.024,0.303,0.000000000,0.017,0.055,2.013,2.184,1.692,0,0.502"
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| 64 | .split(",");
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| 65 | reg[3] = "AgentSmith,-2.075,-0.018,0.333,-0.000000410,0,0.05,1.938,2.027,1.428,0,0.565"
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| 66 | .split(",");
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| 67 | reg[4] = "GYRL,-1.663,0,0.348,0.000000000,0.029,0.028,1.327,1.668,1.327,0,0.609"
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| 68 | .split(",");
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| 69 | reg[5] = "Gahboninho,0.309,-0.024,0.337,0.000000248,0,0,0,0,0.495,0,0.451"
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| 70 | .split(",");
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| 71 | reg[6] = "ValueModelAgent,-1.401,-0.022,0.441,-0.000000206,0,0.044,1.328,1.231,1.629,0,0.49"
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| 72 | .split(",");
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| 73 | reg[7] = "Nice Tit-for-Tat Agent,-0.018,-0.014,0.422,-0.000000381,0,0,0.198,0,0.549,0,0.529"
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| 74 | .split(",");
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| 75 | reg[8] = "HardHeaded,-2.012,-0.035,0.319,0.000000172,0,0.053,2.107,2.136,1.547,0,0.392"
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| 76 | .split(",");
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| 77 | reg[9] = "WinnerAgent,-1.741,0,0.248,0.000000000,0.031,0.03,1.428,1.796,1.742,0,0.599"
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| 78 | .split(",");
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| 79 | reg[10] = "AgentK2,-1.027,-0.012,0.246,0.000000000,0.019,0.022,1.083,1.127,1.097,0,0.531"
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| 80 | .split(",");
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| 81 | reg[11] = "TheNegotiator,-0.159,0.017,0.307,0.000000000,0,0.015,0,0,0.92,0.03,0.665"
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| 82 | .split(",");
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| 83 | reg[12] = "IAMhaggler2011,0.256,0,0.166,0.000000224,0.017,-0.011,0,0,0.347,0,0.543"
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| 84 | .split(",");
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| 85 | reg[13] = "DNAgent,-0.581,-0.024,0.732,0.000000000,0,0.01,0.61,0,1.141,0,0.237"
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| 86 | .split(",");
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| 87 | reg[14] = "BRAMAgent,-0.764,0,0.232,0.000000250,0,0.035,0.842,0.708,0.7,0,0.538"
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| 88 | .split(",");
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| 89 | reg[15] = "MrFriendly,-1.721,-0.025,0.194,-0.000000429,0,0.054,1.814,1.711,1.488,0,0.498"
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| 90 | .split(",");
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| 91 | reg[16] = "ShAgent,-2.072,-0.021,0,0.000000476,0.069,-0.055,2.336,2.805,1.743,0,0.412"
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| 92 | .split(",");
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| 93 | reg[17] = "SimpleAgent,-1.359,0,0.287,-0.000000180,0.028,0.016,1.16,1.524,0.86,0,0.588"
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| 94 | .split(",");
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| 95 | return reg;
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| 96 | }
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| 97 |
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| 98 | private void getDomainParams() {
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| 99 | params = new double[10];
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| 100 | Domain d = this.utilitySpace.getDomain();
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| 101 | List<Issue> a = d.getIssues();
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| 102 |
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| 103 | params[0] = a.size(); // 0 = number of issues.
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| 104 | params[1] = this.utilitySpace.getDiscountFactor() == 0 ? 1
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| 105 | : this.utilitySpace.getDiscountFactor(); // 1
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| 106 | // =
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| 107 | // discount
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| 108 | // factor.
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| 109 | int min = Integer.MAX_VALUE, max = -1, size = 1;
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| 110 |
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| 111 | // params 5+6+7 - Expected Utility of role, Standard deviation of
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| 112 | // Utility of role, Standard deviation of weights of role
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| 113 | double EU = 0, stdevU = 0, stdevW = 0, sW = 0, ssW = 0, countW = 0;
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| 114 | Iterator<Entry<Objective, Evaluator>> issue = ((AdditiveUtilitySpace) utilitySpace)
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| 115 | .getEvaluators().iterator();
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| 116 | List<Double> ssWList = new ArrayList<Double>();
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| 117 | while (issue.hasNext()) { // every issue
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| 118 | Entry<Objective, Evaluator> entry = issue.next();
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| 119 | Evaluator e = entry.getValue();
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| 120 | double weight = e.getWeight();
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| 121 | countW++;
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| 122 | sW += weight;
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| 123 | ssWList.add(weight);
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| 124 | double tempEU = 0, tempStdevU = 0;
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| 125 | if (e.getType() == EVALUATORTYPE.DISCRETE) {
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| 126 | Iterator<ValueDiscrete> v = ((EvaluatorDiscrete) e).getValues()
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| 127 | .iterator();
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| 128 | List<Double> s = new ArrayList<Double>();
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| 129 | double sumU = 0;
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| 130 | while (v.hasNext()) {
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| 131 | ValueDiscrete vd = v.next();
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| 132 | try {
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| 133 | double val = ((EvaluatorDiscrete) e).getEvaluation(vd);
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| 134 | s.add(val);
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| 135 | sumU += val;
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| 136 | } catch (Exception e1) {
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| 137 | e1.printStackTrace();
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| 138 | }
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| 139 | }
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| 140 | int currSize = s.size();
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| 141 | min = (min > currSize) ? currSize : min;
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| 142 | max = (max < currSize) ? currSize : max;
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| 143 | size = size * currSize;
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| 144 | tempEU = sumU / currSize;
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| 145 | Iterator<Double> valIt = s.iterator();
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| 146 | while (valIt.hasNext()) {
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| 147 | tempStdevU += Math.pow(valIt.next() - tempEU, 2);
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| 148 | }
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| 149 | tempStdevU = Math.sqrt(tempStdevU / ((double) currSize - 1));
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| 150 | } else if (e.getType() == EVALUATORTYPE.INTEGER) {
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| 151 | tempEU = ((double) (((EvaluatorInteger) e).getUpperBound()
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| 152 | + ((EvaluatorInteger) e).getLowerBound())) / 2;
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| 153 | tempStdevU = Math.sqrt((Math
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| 154 | .pow(((EvaluatorInteger) e).getUpperBound() - tempEU, 2)
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| 155 | + Math.pow(
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| 156 | ((EvaluatorInteger) e).getLowerBound() - tempEU,
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| 157 | 2))
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| 158 | / 2);
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| 159 | } else if (e.getType() == EVALUATORTYPE.REAL) {
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| 160 | tempEU = (((EvaluatorReal) e).getUpperBound()
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| 161 | + ((EvaluatorReal) e).getLowerBound()) / 2;
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| 162 | tempStdevU = Math.sqrt((Math
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| 163 | .pow(((EvaluatorReal) e).getUpperBound() - tempEU, 2)
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| 164 | + Math.pow(((EvaluatorReal) e).getLowerBound() - tempEU,
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| 165 | 2))
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| 166 | / 2);
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| 167 | } else {
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| 168 | tempEU = 0.5;
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| 169 | tempStdevU = 0;
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| 170 | }
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| 171 |
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| 172 | EU += tempEU * weight;
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| 173 | stdevU += tempStdevU * weight;
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| 174 | }
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| 175 | Iterator<Double> wIt = ssWList.iterator();
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| 176 | double avgW = sW / countW;
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| 177 | while (wIt.hasNext()) {
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| 178 | ssW += Math.pow(wIt.next() - avgW, 2);
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| 179 | }
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| 180 |
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| 181 | stdevW = countW <= 1 ? 0 : Math.sqrt(ssW / (countW - 1));
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| 182 | params[2] = size;
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| 183 | params[3] = min;
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| 184 | params[4] = max;
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| 185 | params[5] = EU;
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| 186 | params[6] = stdevU;
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| 187 | params[7] = stdevW;
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| 188 | params[8] = first ? 1 : 0;
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| 189 | params[9] = opponentFirstBid;
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| 190 | }
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| 191 |
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| 192 | private String getBestAgent() {
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| 193 | double lambda = 70;
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| 194 | double sumExp = 0;
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| 195 |
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| 196 | String ans = null;
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| 197 | getDomainParams();
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| 198 | String[][] reg = getRegression();
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| 199 | double maxResult = 0;
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| 200 | int bestIndex = -1;
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| 201 | List<String> agents = new ArrayList<String>();
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| 202 | double[] agentsResults = new double[reg.length];
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| 203 | for (int k = 0; k < reg.length; k++) {
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| 204 | agents.add(k, reg[k][0]);
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| 205 | double regressionResult = 0;
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| 206 | double[] regression = new double[params.length + 1];
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| 207 |
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| 208 | for (int i = 0; i < regression.length; i++) {
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| 209 | regression[i] = Double.parseDouble(reg[k][i + 1]);
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| 210 | if (i > 0) {
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| 211 | regressionResult += regression[i] * params[i - 1];
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| 212 | } else
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| 213 | regressionResult += regression[i];
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| 214 | }
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| 215 | if (!(reg[k][0].equalsIgnoreCase("Nice Tit-for-Tat Agent")
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| 216 | || reg[k][0].equalsIgnoreCase("IAMhaggler2011")
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| 217 | || reg[k][0].equalsIgnoreCase("IAMcrazyhaggler"))) {
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| 218 | // calculate QRE value, part 1
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| 219 | agentsResults[k] = Math.exp(regressionResult * lambda);
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| 220 | } else // 3 agents that doesn't work - will get a 0 value.
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| 221 | {
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| 222 | agentsResults[k] = 0;
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| 223 | }
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| 224 | sumExp += agentsResults[k];
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| 225 |
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| 226 | }
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| 227 | double rand = Math.random(), totalValue = 0;
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| 228 | for (int i = 0; i < agentsResults.length; i++) {
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| 229 | // calculate QRE value, part 2
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| 230 | agentsResults[i] = agentsResults[i] / sumExp;
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| 231 | totalValue += agentsResults[i];
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| 232 | if (rand < totalValue) { // at the end, total value will be 1 (it's
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| 233 | // a probability value)
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| 234 | bestIndex = i;
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| 235 | break;
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| 236 | }
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| 237 | }
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| 238 |
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| 239 | ans = agents.get(bestIndex);
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| 240 | myAgentName = ans;
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| 241 | return ans;
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| 242 |
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| 243 | }
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| 244 |
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| 245 | private Agent selectAgent(String name) {
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| 246 | Agent a = new KLH(); // default, as winner of 2011 contest.
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| 247 | if (name.equalsIgnoreCase("IAMcrazyhaggler"))
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| 248 | return a;// /agent doesn't work
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| 249 | else if (name.equalsIgnoreCase("LYYAgent"))
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| 250 | return new LYYAgent();
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| 251 | else if (name.equalsIgnoreCase("Chameleon"))
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| 252 | return new Chameleon();
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| 253 | else if (name.equalsIgnoreCase("AgentSmith"))
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| 254 | return new AgentSmith();
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| 255 | else if (name.equalsIgnoreCase("GYRL"))
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| 256 | return new GYRL();
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| 257 | else if (name.equalsIgnoreCase("Gahboninho"))
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| 258 | return new Gahboninho();
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| 259 | else if (name.equalsIgnoreCase("ValueModelAgent"))
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| 260 | return new ValueModelAgent();
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| 261 | else if (name.equalsIgnoreCase("Nice Tit-for-Tat Agent"))
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| 262 | return a;// /agent doesn't work
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| 263 | else if (name.equalsIgnoreCase("HardHeaded"))
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| 264 | return new KLH();
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| 265 | else if (name.equalsIgnoreCase("WinnerAgent"))
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| 266 | return new WinnerAgent2();
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| 267 | else if (name.equalsIgnoreCase("AgentK2"))
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| 268 | return new Agent_K2();
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| 269 | else if (name.equalsIgnoreCase("TheNegotiator"))
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| 270 | return new TheNegotiator();
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| 271 | else if (name.equalsIgnoreCase("IAMhaggler2011"))
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| 272 | return a;// /agent doesn't work
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| 273 | else if (name.equalsIgnoreCase("DNAgent"))
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| 274 | return new DNAgent();
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| 275 | else if (name.equalsIgnoreCase("BRAMAgent"))
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| 276 | return new BRAMAgent();
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| 277 | else if (name.equalsIgnoreCase("MrFriendly"))
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| 278 | return new MrFriendly();
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| 279 | else if (name.equalsIgnoreCase("ShAgent"))
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| 280 | return new ShAgent();
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| 281 | else if (name.equalsIgnoreCase("simpleAgent"))
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| 282 | return new SimpleAgentNew();
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| 283 | else
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| 284 | return a;
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| 285 |
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| 286 | }
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| 287 |
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| 288 | @Override
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| 289 | public Action chooseAction() {
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| 290 | try {
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| 291 | if (!agentInit) {
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| 292 | if (actionOfPartner == null) // first bid, and Meta-Agent is the
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| 293 | // first bidder (still not
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| 294 | // initialized any agent)
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| 295 | {
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| 296 | first = true;
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| 297 | return new Offer(this.getAgentID(),
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| 298 | utilitySpace.getMaxUtilityBid());
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| 299 | } else // second bid, or first bid as responder (and not
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| 300 | // initiator)
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| 301 | {
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| 302 | agentInit = true;
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| 303 | if (actionOfPartner instanceof Offer) {
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| 304 | opponentFirstBid = utilitySpace
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| 305 | .getUtility(((Offer) actionOfPartner).getBid());
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| 306 | }
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| 307 |
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| 308 | // initialize agent.
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| 309 | myAgent = selectAgent(getBestAgent());
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| 310 | myAgent.internalInit(0, 1, this.startTime, this.totalTime,
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| 311 | this.timeline, this.utilitySpace,
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| 312 | this.parametervalues, getAgentID());
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| 313 | myAgent.init();
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| 314 | // send the message that received to the new agent..
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| 315 | myAgent.ReceiveMessage(actionOfPartner);
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| 316 | }
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| 317 | }
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| 318 | Action a = myAgent.chooseAction();
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| 319 | if (a == null) {
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| 320 | return new Offer(this.getAgentID(),
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| 321 | utilitySpace.getMaxUtilityBid());
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| 322 | } else { // handle reservation value, because all agent are from
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| 323 | // Genius version 3.1 (and don't know what is
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| 324 | // reservation value)
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| 325 | double time = timeline.getTime();
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| 326 | if (a instanceof Offer
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| 327 | && this.utilitySpace.getReservationValueWithDiscount(
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| 328 | time) >= utilitySpace.getUtilityWithDiscount(
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| 329 | ((Offer) a).getBid(), time)) {
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| 330 | a = new EndNegotiation(getAgentID());
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| 331 | }
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| 332 |
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| 333 | }
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| 334 | return a;
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| 335 |
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| 336 | } catch (Exception e) {
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| 337 | return null;
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| 338 | }
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| 339 | }
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| 340 |
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| 341 | @Override
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| 342 | public void ReceiveMessage(Action opponentAction) {
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| 343 | actionOfPartner = opponentAction;
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| 344 | if (agentInit)
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| 345 | myAgent.ReceiveMessage(opponentAction);
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| 346 | }
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| 347 |
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| 348 | @Override
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| 349 | public String getName() {
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| 350 | if (myAgentName == null || myAgentName == "")
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| 351 | return "Meta-Agent 2012";
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| 352 | else
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| 353 | return "Meta-Agent 2012: " + myAgentName;
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| 354 | }
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| 355 |
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| 356 | @Override
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| 357 | public String getVersion() {
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| 358 | return "1.42";
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| 359 | }
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| 360 |
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| 361 | @Override
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| 362 | public SupportedNegotiationSetting getSupportedNegotiationSetting() {
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| 363 | return SupportedNegotiationSetting.getLinearUtilitySpaceInstance();
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| 364 | }
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| 365 |
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| 366 | @Override
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| 367 | public String getDescription() {
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| 368 | return "ANAC2012";
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| 369 | }
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| 370 | }
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