[127] | 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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