[3] | 1 | package ai2020.group6;
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| 2 |
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| 3 | import java.math.BigDecimal;
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| 4 |
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| 5 | import geniusweb.inform.Settings;
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| 6 |
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| 7 | /**
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| 8 | * MAMirroredExponential accepts and generates bids above a threshold exponentially
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| 9 | * decreasing as a function of time.
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| 10 | * The threshold starts at the "upperThreshold" (defaulting to 1) and decreases
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| 11 | * to the "lowerThreshold" (defaulting to 0) by scaling with 1-t^(1/e), where t is
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| 12 | * the progress over time and e is the parameter "e" (defaulting to 1).
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| 13 | *
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| 14 | * This is the default behaviour of the exampleparties provided by the geniusweb
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| 15 | * framework;
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| 16 | * Hardliner: e = 0'
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| 17 | * Boulware: e = 0.2
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| 18 | * Linear: e = 1
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| 19 | * TimeDependentParty: e = 1.2
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| 20 | * Conceder: e = 2
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| 21 | *
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| 22 | * ' e = 0 would theoretically give the same result, but is not allowed for this agent,
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| 23 | * as this would leave this agent with a static threshold of "upperThreshold" and
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| 24 | * is therefore replaceable with the MAStatic agent.
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| 25 | *
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| 26 | * @author Group 6
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| 27 | */
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| 28 | public class MAMirroredExponential extends MADefaultParty {
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| 29 |
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| 30 | @Override
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| 31 | protected IAcceptanceStrategy getAccceptanceStrategy ( Settings settings ) {
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| 32 | Object val = settings.getParameters().get("minPower");
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| 33 | Integer minpower = (val instanceof Integer) ? (Integer) val : 2;
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| 34 | val = settings.getParameters().get("maxPower");
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| 35 | Integer maxpower = (val instanceof Integer) ? (Integer) val : Integer.MAX_VALUE;
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| 36 | val = settings.getParameters().get("upperThreshold");
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| 37 | Double upperThreshold = (val instanceof Double) ? (Double) val : 1.0;
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| 38 | val = settings.getParameters().get("lowerThreshold");
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| 39 | Double lowerThreshold = (val instanceof Double) ? (Double) val : 0.0;
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| 40 | val = settings.getParameters().get("e");
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| 41 | Double e = (val instanceof Double) ? (Double) val : 1.0;
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| 42 | return new UtilityBasedAcceptanceStrategy(minpower, maxpower) {
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| 43 | @Override
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| 44 | public BigDecimal getUtilityThreshold ( MAState state ) {
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| 45 | Double t = state.getProgressTime().doubleValue();
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| 46 | Double scale = 1-Math.pow(t, 1/e);
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| 47 | return BigDecimal.valueOf(lowerThreshold + scale * (upperThreshold - lowerThreshold));
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| 48 | }
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| 49 | };
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| 50 | }
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| 51 |
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| 52 | @Override
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| 53 | protected IBiddingStrategy getBiddingStrategy ( Settings settings ) {
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| 54 | Object val = settings.getParameters().get("minPower");
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| 55 | Integer minpower = (val instanceof Integer) ? (Integer) val : 2;
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| 56 | val = settings.getParameters().get("maxPower");
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| 57 | Integer maxpower = (val instanceof Integer) ? (Integer) val : Integer.MAX_VALUE;
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| 58 | val = settings.getParameters().get("upperThreshold");
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| 59 | Double upperThreshold = (val instanceof Double) ? (Double) val : 1.0;
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| 60 | val = settings.getParameters().get("lowerThreshold");
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| 61 | Double lowerThreshold = (val instanceof Double) ? (Double) val : 0.0;
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| 62 | val = settings.getParameters().get("e");
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| 63 | Double e = (val instanceof Double) ? (Double) val : 1.0;
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| 64 | return new UtilityBasedBiddingStrategy(minpower, maxpower) {
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| 65 | @Override
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| 66 | public BigDecimal getUpperUtilityThreshold ( MAState state ) {
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| 67 | return BigDecimal.valueOf(upperThreshold);
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| 68 | }
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| 69 | @Override
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| 70 | public BigDecimal getLowerUtilityThreshold ( MAState state ) {
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| 71 | Double t = state.getProgressTime().doubleValue();
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| 72 | Double scale = 1-Math.pow(t, 1/e);
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| 73 | return BigDecimal.valueOf(lowerThreshold + scale * (upperThreshold - lowerThreshold));
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| 74 | }
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| 75 | };
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| 76 | }
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| 77 |
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| 78 | @Override
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| 79 | protected IOptInStrategy getOptInStrategy ( Settings settings ) {
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| 80 | return new NoOptInStrategy();
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| 81 | }
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| 82 |
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| 83 | // @Override
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| 84 | // protected IOpponentModel initNewOpponentModel ( Settings settings ) {
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| 85 | // return new EmptyOpponentModel();
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| 86 | // }
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| 87 |
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| 88 | }
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