[6152] | 1 | /* |
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| 2 | Copyright 2006 by Sean Luke |
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| 3 | Licensed under the Academic Free License version 3.0 |
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| 4 | See the file "LICENSE" for more information |
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| 5 | */ |
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| 6 | |
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| 7 | |
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| 8 | package ec.select; |
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| 9 | import ec.*; |
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| 10 | import ec.util.*; |
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| 11 | import ec.steadystate.*; |
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| 12 | |
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| 13 | /* |
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| 14 | * TournamentSelection.java |
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| 15 | * |
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| 16 | * Created: Mon Aug 30 19:27:15 1999 |
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| 17 | * By: Sean Luke |
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| 18 | */ |
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| 19 | |
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| 20 | /** |
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| 21 | * Does a simple tournament selection, limited to the subpopulation it's |
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| 22 | * working in at the time. |
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| 23 | * |
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| 24 | * <p>Tournament selection works like this: first, <i>size</i> individuals |
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| 25 | * are chosen at random from the population. Then of those individuals, |
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| 26 | * the one with the best fitness is selected. |
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| 27 | * |
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| 28 | * <p><i>size</i> can also be a floating-point value between 1.0 and 2.0, |
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| 29 | * exclusive of them. In this situation, two individuals are chosen at random, and |
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| 30 | * the better one is selected with a probability of <i>size/2</i> |
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| 31 | * |
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| 32 | * <p>Common sizes for <i>size</i> include: 2, popular in Genetic Algorithms |
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| 33 | * circles, and 7, popularized in Genetic Programming by John Koza. |
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| 34 | * If the size is 1, then individuals are picked entirely at random. |
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| 35 | * |
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| 36 | * <p>Tournament selection is so simple that it doesn't need to maintain |
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| 37 | * a cache of any form, so many of the SelectionMethod methods just |
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| 38 | * don't do anything at all. |
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| 39 | * |
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| 40 | |
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| 41 | <p><b>Typical Number of Individuals Produced Per <tt>produce(...)</tt> call</b><br> |
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| 42 | Always 1. |
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| 43 | |
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| 44 | <p><b>Parameters</b><br> |
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| 45 | <table> |
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| 46 | <tr><td valign=top><i>base.</i><tt>size</tt><br> |
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| 47 | <font size=-1>float >= 1</font></td> |
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| 48 | <td valign=top>(the tournament size)</td></tr> |
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| 49 | |
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| 50 | <tr><td valign=top><i>base.</i><tt>pick-worst</tt><br> |
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| 51 | <font size=-1> bool = <tt>true</tt> or <tt>false</tt> (default)</font></td> |
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| 52 | <td valign=top>(should we pick the <i>worst</i> individual in the tournament instead of the <i>best</i>?)</td></tr> |
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| 53 | |
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| 54 | </table> |
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| 55 | |
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| 56 | <p><b>Default Base</b><br> |
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| 57 | select.tournament |
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| 58 | |
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| 59 | * |
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| 60 | * @author Sean Luke |
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| 61 | * @version 1.0 |
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| 62 | */ |
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| 63 | |
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| 64 | public class TournamentSelection extends SelectionMethod implements SteadyStateBSourceForm |
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| 65 | { |
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| 66 | /** default base */ |
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| 67 | public static final String P_TOURNAMENT = "tournament"; |
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| 68 | |
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| 69 | public static final String P_PICKWORST = "pick-worst"; |
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| 70 | |
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| 71 | /** size parameter */ |
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| 72 | public static final String P_SIZE = "size"; |
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| 73 | |
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| 74 | /* Default size */ |
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| 75 | public static final int DEFAULT_SIZE = 7; |
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| 76 | |
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| 77 | /** Base size of the tournament; this may change. */ |
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| 78 | int size; |
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| 79 | |
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| 80 | /** Probablity of picking the size plus one */ |
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| 81 | public double probabilityOfPickingSizePlusOne; |
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| 82 | |
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| 83 | /** Do we pick the worst instead of the best? */ |
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| 84 | public boolean pickWorst; |
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| 85 | |
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| 86 | public Parameter defaultBase() |
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| 87 | { |
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| 88 | return SelectDefaults.base().push(P_TOURNAMENT); |
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| 89 | } |
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| 90 | |
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| 91 | public void setup(final EvolutionState state, final Parameter base) |
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| 92 | { |
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| 93 | super.setup(state,base); |
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| 94 | |
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| 95 | Parameter def = defaultBase(); |
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| 96 | |
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| 97 | double val = state.parameters.getDouble(base.push(P_SIZE),def.push(P_SIZE),1.0); |
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| 98 | if (val < 1.0) |
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| 99 | state.output.fatal("Tournament size must be >= 1.",base.push(P_SIZE),def.push(P_SIZE)); |
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| 100 | else if (val == (int) val) // easy, it's just an integer |
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| 101 | { |
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| 102 | size = (int) val; |
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| 103 | probabilityOfPickingSizePlusOne = 0.0; |
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| 104 | } |
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| 105 | else |
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| 106 | { |
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| 107 | size = (int) Math.floor(val); |
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| 108 | probabilityOfPickingSizePlusOne = val - size; // for example, if we have 5.4, then the probability of picking *6* is 0.4 |
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| 109 | } |
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| 110 | |
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| 111 | pickWorst = state.parameters.getBoolean(base.push(P_PICKWORST),def.push(P_PICKWORST),false); |
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| 112 | } |
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| 113 | |
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| 114 | /** Returns a tournament size to use, at random, based on base size and probability of picking the size plus one. */ |
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| 115 | public int getTournamentSizeToUse(MersenneTwisterFast random) |
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| 116 | { |
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| 117 | double p = probabilityOfPickingSizePlusOne; // pulls us to under 35 bytes |
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| 118 | if (p == 0.0) return size; |
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| 119 | return size + (random.nextBoolean(p) ? 1 : 0); |
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| 120 | } |
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| 121 | |
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| 122 | |
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| 123 | /** Produces the index of a (typically uniformly distributed) randomly chosen individual |
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| 124 | to fill the tournament. <i>number</> is the position of the individual in the tournament. */ |
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| 125 | public int getRandomIndividual(int number, int subpopulation, EvolutionState state, int thread) |
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| 126 | { |
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| 127 | Individual[] oldinds = state.population.subpops[subpopulation].individuals; |
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| 128 | return state.random[thread].nextInt(oldinds.length); |
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| 129 | } |
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| 130 | |
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| 131 | /** Returns true if *first* is a better (fitter, whatever) individual than *second*. */ |
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| 132 | public boolean betterThan(Individual first, Individual second, int subpopulation, EvolutionState state, int thread) |
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| 133 | { |
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| 134 | return first.fitness.betterThan(second.fitness); |
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| 135 | } |
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| 136 | |
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| 137 | public int produce(final int subpopulation, |
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| 138 | final EvolutionState state, |
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| 139 | final int thread) |
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| 140 | { |
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| 141 | // pick size random individuals, then pick the best. |
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| 142 | Individual[] oldinds = state.population.subpops[subpopulation].individuals; |
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| 143 | int best = getRandomIndividual(0, subpopulation, state, thread); |
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| 144 | |
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| 145 | int s = getTournamentSizeToUse(state.random[thread]); |
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| 146 | |
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| 147 | if (pickWorst) |
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| 148 | for (int x=1;x<s;x++) |
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| 149 | { |
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| 150 | int j = getRandomIndividual(x, subpopulation, state, thread); |
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| 151 | if (!betterThan(oldinds[j], oldinds[best], subpopulation, state, thread)) // j is at least as bad as best |
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| 152 | best = j; |
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| 153 | } |
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| 154 | else |
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| 155 | for (int x=1;x<s;x++) |
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| 156 | { |
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| 157 | int j = getRandomIndividual(x, subpopulation, state, thread); |
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| 158 | if (betterThan(oldinds[j], oldinds[best], subpopulation, state, thread)) // j is better than best |
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| 159 | best = j; |
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| 160 | } |
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| 161 | |
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| 162 | return best; |
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| 163 | } |
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| 164 | |
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| 165 | // included for SteadyState |
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| 166 | public void individualReplaced(final SteadyStateEvolutionState state, |
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| 167 | final int subpopulation, |
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| 168 | final int thread, |
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| 169 | final int individual) |
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| 170 | { return; } |
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| 171 | |
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| 172 | public void sourcesAreProperForm(final SteadyStateEvolutionState state) |
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| 173 | { return; } |
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| 174 | |
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| 175 | } |
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