Last change
on this file since 12417 was
11832,
checked in by gkronber, 10 years ago
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linear value function approximation and good results for poly-10 benchmark
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File size:
1.6 KB
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1 | using System;
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2 | using System.Collections.Generic;
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3 | using System.Diagnostics;
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4 | using System.Linq;
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5 | using System.Text;
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6 | using System.Threading.Tasks;
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7 | using HeuristicLab.Common;
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8 |
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9 | namespace HeuristicLab.Algorithms.Bandits.BanditPolicies {
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10 | public class UCBNormalPolicy : IBanditPolicy {
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11 |
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12 | public int SelectAction(Random random, IEnumerable<IBanditPolicyActionInfo> actionInfos) {
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13 | var myActionInfos = actionInfos.OfType<MeanAndVariancePolicyActionInfo>();
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14 | int totalTries = myActionInfos.Sum(a => a.Tries);
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15 | double bestQ = double.NegativeInfinity;
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16 | int aIdx = -1;
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17 | var bestActions = new List<int>();
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18 | foreach (var aInfo in myActionInfos) {
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19 | aIdx++;
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20 | double q;
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21 | if (totalTries <= 1 || aInfo.Tries <= 1 || aInfo.Tries <= Math.Ceiling(8 * Math.Log(totalTries))) {
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22 | q = double.PositiveInfinity;
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23 | } else {
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24 | var tries = aInfo.Tries;
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25 | var avgReward = aInfo.AvgReward;
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26 | var rewardVariance = aInfo.RewardVariance;
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27 | var estVariance = 16.0 * rewardVariance * (Math.Log(totalTries - 1) / tries);
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28 | q = avgReward + Math.Sqrt(estVariance);
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29 | }
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30 | if (q > bestQ) {
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31 | bestQ = q;
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32 | bestActions.Clear();
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33 | bestActions.Add(aIdx);
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34 | } else if (q.IsAlmost(bestQ)) {
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35 | bestActions.Add(aIdx);
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36 | }
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37 | }
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38 | Debug.Assert(bestActions.Any());
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39 | return bestActions.SelectRandom(random);
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40 | }
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41 |
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42 | public IBanditPolicyActionInfo CreateActionInfo() {
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43 | return new MeanAndVariancePolicyActionInfo();
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44 | }
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45 |
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46 | public override string ToString() {
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47 | return "UCBNormalPolicy";
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48 | }
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49 | }
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50 | }
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