source: branches/HeuristicLab.Problems.GrammaticalOptimization/HeuristicLab.Problems.GrammaticalOptimization.Test/TestBanditPolicies.cs @ 11730

using System;
using System.Linq;
using System.Collections.Generic;
using System.Globalization;
using HeuristicLab.Algorithms.Bandits;
using HeuristicLab.Algorithms.Bandits.Models;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace HeuristicLab.Problems.GrammaticalOptimization.Test {
  [TestClass]
  public class TestBanditPolicies {


    [TestMethod]
    public void ComparePoliciesForBernoulliBandit() {
      CultureInfo.DefaultThreadCurrentCulture = CultureInfo.InvariantCulture;

      var globalRand = new Random(31415);
      var seedForPolicy = globalRand.Next();
      var nArms = 20;
      //Console.WriteLine("Exp3 (gamma=0.01)");
      //TestPolicyBernoulli(globalRand, nArms, new Exp3Policy(new Random(seedForPolicy), nArms, 1));
      //Console.WriteLine("Exp3 (gamma=0.05)");
      //estPolicyBernoulli(globalRand, nArms, new Exp3Policy(new Random(seedForPolicy), nArms, 1));
      Console.WriteLine("Thompson (Bernoulli)"); TestPolicyBernoulli(globalRand, nArms, new BernoulliThompsonSamplingPolicy(new Random(seedForPolicy), nArms));
      Console.WriteLine("Generic Thompson (Bernoulli)"); TestPolicyBernoulli(globalRand, nArms, new GenericThompsonSamplingPolicy(new Random(seedForPolicy), nArms, new BernoulliModel(nArms)));
      Console.WriteLine("Random");
      TestPolicyBernoulli(globalRand, nArms, new RandomPolicy(new Random(seedForPolicy), nArms));
      Console.WriteLine("UCB1");
      TestPolicyBernoulli(globalRand, nArms, new UCB1Policy(nArms));
      Console.WriteLine("UCB1Tuned");
      TestPolicyBernoulli(globalRand, nArms, new UCB1TunedPolicy(nArms));
      Console.WriteLine("UCB1Normal");
      TestPolicyBernoulli(globalRand, nArms, new UCBNormalPolicy(nArms));
      Console.WriteLine("Eps(0.01)");
      TestPolicyBernoulli(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.01));
      Console.WriteLine("Eps(0.05)");
      TestPolicyBernoulli(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.05));
      //Console.WriteLine("Eps(0.1)");
      //TestPolicyBernoulli(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.1));
      //Console.WriteLine("Eps(0.2)");
      //TestPolicyBernoulli(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.2));
      //Console.WriteLine("Eps(0.5)");
      //TestPolicyBernoulli(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.5));
      Console.WriteLine("UCT(0.1)"); TestPolicyBernoulli(globalRand, nArms, new UCTPolicy(nArms, 0.1));
      Console.WriteLine("UCT(0.5)"); TestPolicyBernoulli(globalRand, nArms, new UCTPolicy(nArms, 0.5));
      Console.WriteLine("UCT(1)  "); TestPolicyBernoulli(globalRand, nArms, new UCTPolicy(nArms, 1));
      Console.WriteLine("UCT(2)  "); TestPolicyBernoulli(globalRand, nArms, new UCTPolicy(nArms, 2));
      Console.WriteLine("UCT(5)  "); TestPolicyBernoulli(globalRand, nArms, new UCTPolicy(nArms, 5));
      Console.WriteLine("BoltzmannExploration(0.1)"); TestPolicyBernoulli(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 0.1));
      Console.WriteLine("BoltzmannExploration(0.5)"); TestPolicyBernoulli(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 0.5));
      Console.WriteLine("BoltzmannExploration(1)  "); TestPolicyBernoulli(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 1));
      Console.WriteLine("BoltzmannExploration(10) "); TestPolicyBernoulli(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 10));
      Console.WriteLine("BoltzmannExploration(100)"); TestPolicyBernoulli(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 100));
      Console.WriteLine("ChernoffIntervalEstimationPolicy(0.01)"); TestPolicyBernoulli(globalRand, nArms, new ChernoffIntervalEstimationPolicy(nArms, 0.01));
      Console.WriteLine("ChernoffIntervalEstimationPolicy(0.05)"); TestPolicyBernoulli(globalRand, nArms, new ChernoffIntervalEstimationPolicy(nArms, 0.05));
      Console.WriteLine("ChernoffIntervalEstimationPolicy(0.1) "); TestPolicyBernoulli(globalRand, nArms, new ChernoffIntervalEstimationPolicy(nArms, 0.1));

      // not applicable to bernoulli rewards
      //Console.WriteLine("ThresholdAscent(10, 0.01)  "); TestPolicyBernoulli(globalRand, nArms, new ThresholdAscentPolicy(nArms, 10, 0.01));
      //Console.WriteLine("ThresholdAscent(10, 0.05)  "); TestPolicyBernoulli(globalRand, nArms, new ThresholdAscentPolicy(nArms, 10, 0.05));
      //Console.WriteLine("ThresholdAscent(10, 0.1)   "); TestPolicyBernoulli(globalRand, nArms, new ThresholdAscentPolicy(nArms, 10, 0.1));
      //Console.WriteLine("ThresholdAscent(100, 0.01) "); TestPolicyBernoulli(globalRand, nArms, new ThresholdAscentPolicy(nArms, 100, 0.01));
      //Console.WriteLine("ThresholdAscent(100, 0.05) "); TestPolicyBernoulli(globalRand, nArms, new ThresholdAscentPolicy(nArms, 100, 0.05));
      //Console.WriteLine("ThresholdAscent(100, 0.1)  "); TestPolicyBernoulli(globalRand, nArms, new ThresholdAscentPolicy(nArms, 100, 0.1));
      //Console.WriteLine("ThresholdAscent(1000, 0.01)"); TestPolicyBernoulli(globalRand, nArms, new ThresholdAscentPolicy(nArms, 1000, 0.01));
      //Console.WriteLine("ThresholdAscent(1000, 0.05)"); TestPolicyBernoulli(globalRand, nArms, new ThresholdAscentPolicy(nArms, 1000, 0.05));
      //Console.WriteLine("ThresholdAscent(1000, 0.1) "); TestPolicyBernoulli(globalRand, nArms, new ThresholdAscentPolicy(nArms, 1000, 0.1));
    }

    [TestMethod]
    public void ComparePoliciesForNormalBandit() {
      CultureInfo.DefaultThreadCurrentCulture = CultureInfo.InvariantCulture;

      var globalRand = new Random(31415);
      var seedForPolicy = globalRand.Next();
      var nArms = 20;
      Console.WriteLine("Thompson (Gaussian orig)"); TestPolicyNormal(globalRand, nArms, new GaussianThompsonSamplingPolicy(new Random(seedForPolicy), nArms, true));
      Console.WriteLine("Thompson (Gaussian new)"); TestPolicyNormal(globalRand, nArms, new GaussianThompsonSamplingPolicy(new Random(seedForPolicy), nArms));
      Console.WriteLine("Generic Thompson (Gaussian)"); TestPolicyNormal(globalRand, nArms, new GenericThompsonSamplingPolicy(new Random(seedForPolicy), nArms, new GaussianModel(nArms, 0.5, 1)));
      /*
      Console.WriteLine("Random"); TestPolicyNormal(globalRand, nArms, new RandomPolicy(new Random(seedForPolicy), nArms));
      Console.WriteLine("UCB1"); TestPolicyNormal(globalRand, nArms, new UCB1Policy(nArms));
      Console.WriteLine("UCB1Tuned"); TestPolicyNormal(globalRand, nArms, new UCB1TunedPolicy(nArms));
      Console.WriteLine("UCB1Normal"); TestPolicyNormal(globalRand, nArms, new UCBNormalPolicy(nArms));
      //Console.WriteLine("Exp3 (gamma=0.01)");
      //TestPolicyNormal(globalRand, nArms, new Exp3Policy(new Random(seedForPolicy), nArms, 0.01));
      //Console.WriteLine("Exp3 (gamma=0.05)");
      //TestPolicyNormal(globalRand, nArms, new Exp3Policy(new Random(seedForPolicy), nArms, 0.05));
      Console.WriteLine("Eps(0.01)"); TestPolicyNormal(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.01));
      Console.WriteLine("Eps(0.05)"); TestPolicyNormal(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.05));
      //Console.WriteLine("Eps(0.1)");
      //TestPolicyNormal(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.1));
      //Console.WriteLine("Eps(0.2)");
      //TestPolicyNormal(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.2));
      //Console.WriteLine("Eps(0.5)");
      //TestPolicyNormal(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.5));
      Console.WriteLine("UCT(0.1)"); TestPolicyNormal(globalRand, nArms, new UCTPolicy(nArms, 0.1));
      Console.WriteLine("UCT(0.5)"); TestPolicyNormal(globalRand, nArms, new UCTPolicy(nArms, 0.5));
      Console.WriteLine("UCT(1)  "); TestPolicyNormal(globalRand, nArms, new UCTPolicy(nArms, 1));
      Console.WriteLine("UCT(2)  "); TestPolicyNormal(globalRand, nArms, new UCTPolicy(nArms, 2));
      Console.WriteLine("UCT(5)  "); TestPolicyNormal(globalRand, nArms, new UCTPolicy(nArms, 5));
      Console.WriteLine("BoltzmannExploration(0.1)"); TestPolicyNormal(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 0.1));
      Console.WriteLine("BoltzmannExploration(0.5)"); TestPolicyNormal(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 0.5));
      Console.WriteLine("BoltzmannExploration(1)  "); TestPolicyNormal(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 1));
      Console.WriteLine("BoltzmannExploration(10) "); TestPolicyNormal(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 10));
      Console.WriteLine("BoltzmannExploration(100)"); TestPolicyNormal(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 100));
      Console.WriteLine("ChernoffIntervalEstimationPolicy(0.01)"); TestPolicyNormal(globalRand, nArms, new ChernoffIntervalEstimationPolicy(nArms, 0.01));
      Console.WriteLine("ChernoffIntervalEstimationPolicy(0.05)"); TestPolicyNormal(globalRand, nArms, new ChernoffIntervalEstimationPolicy(nArms, 0.05));
      Console.WriteLine("ChernoffIntervalEstimationPolicy(0.1) "); TestPolicyNormal(globalRand, nArms, new ChernoffIntervalEstimationPolicy(nArms, 0.1));
      Console.WriteLine("ThresholdAscent(10,0.01)  "); TestPolicyNormal(globalRand, nArms, new ThresholdAscentPolicy(nArms, 10, 0.01));
      Console.WriteLine("ThresholdAscent(10,0.05)  "); TestPolicyNormal(globalRand, nArms, new ThresholdAscentPolicy(nArms, 10, 0.05));
      Console.WriteLine("ThresholdAscent(10,0.1)   "); TestPolicyNormal(globalRand, nArms, new ThresholdAscentPolicy(nArms, 10, 0.1));
      Console.WriteLine("ThresholdAscent(100,0.01) "); TestPolicyNormal(globalRand, nArms, new ThresholdAscentPolicy(nArms, 100, 0.01));
      Console.WriteLine("ThresholdAscent(100,0.05) "); TestPolicyNormal(globalRand, nArms, new ThresholdAscentPolicy(nArms, 100, 0.05));
      Console.WriteLine("ThresholdAscent(100,0.1)  "); TestPolicyNormal(globalRand, nArms, new ThresholdAscentPolicy(nArms, 100, 0.1));
      Console.WriteLine("ThresholdAscent(1000,0.01)"); TestPolicyNormal(globalRand, nArms, new ThresholdAscentPolicy(nArms, 1000, 0.01));
      Console.WriteLine("ThresholdAscent(1000,0.05)"); TestPolicyNormal(globalRand, nArms, new ThresholdAscentPolicy(nArms, 1000, 0.05));
      Console.WriteLine("ThresholdAscent(1000,0.1) "); TestPolicyNormal(globalRand, nArms, new ThresholdAscentPolicy(nArms, 1000, 0.1));
       */
    }

    [TestMethod]
    public void ComparePoliciesForGaussianMixtureBandit() {
      CultureInfo.DefaultThreadCurrentCulture = CultureInfo.InvariantCulture;

      var globalRand = new Random(31415);
      var seedForPolicy = globalRand.Next();
      var nArms = 20;
      Console.WriteLine("Thompson (Gaussian orig)"); TestPolicyGaussianMixture(globalRand, nArms, new GaussianThompsonSamplingPolicy(new Random(seedForPolicy), nArms, true));
      Console.WriteLine("Thompson (Gaussian new)"); TestPolicyGaussianMixture(globalRand, nArms, new GaussianThompsonSamplingPolicy(new Random(seedForPolicy), nArms));
      Console.WriteLine("Generic Thompson (Gaussian)"); TestPolicyGaussianMixture(globalRand, nArms, new GenericThompsonSamplingPolicy(new Random(seedForPolicy), nArms, new GaussianModel(nArms, 0.5, 1)));

      /*
      Console.WriteLine("Random"); TestPolicyGaussianMixture(globalRand, nArms, new RandomPolicy(new Random(seedForPolicy), nArms));
      Console.WriteLine("UCB1"); TestPolicyGaussianMixture(globalRand, nArms, new UCB1Policy(nArms));
      Console.WriteLine("UCB1Tuned "); TestPolicyGaussianMixture(globalRand, nArms, new UCB1TunedPolicy(nArms));
      Console.WriteLine("UCB1Normal"); TestPolicyGaussianMixture(globalRand, nArms, new UCBNormalPolicy(nArms));
      Console.WriteLine("Eps(0.01) "); TestPolicyGaussianMixture(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.01));
      Console.WriteLine("Eps(0.05) "); TestPolicyGaussianMixture(globalRand, nArms, new EpsGreedyPolicy(new Random(seedForPolicy), nArms, 0.05));
      Console.WriteLine("UCT(1)  "); TestPolicyGaussianMixture(globalRand, nArms, new UCTPolicy(nArms, 1));
      Console.WriteLine("UCT(2)  "); TestPolicyGaussianMixture(globalRand, nArms, new UCTPolicy(nArms, 2));
      Console.WriteLine("UCT(5)  "); TestPolicyGaussianMixture(globalRand, nArms, new UCTPolicy(nArms, 5));
      Console.WriteLine("BoltzmannExploration(1)  "); TestPolicyGaussianMixture(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 1));
      Console.WriteLine("BoltzmannExploration(10) "); TestPolicyGaussianMixture(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 10));
      Console.WriteLine("BoltzmannExploration(100)"); TestPolicyGaussianMixture(globalRand, nArms, new BoltzmannExplorationPolicy(new Random(seedForPolicy), nArms, 100));

      Console.WriteLine("ThresholdAscent(10,0.01)  "); TestPolicyGaussianMixture(globalRand, nArms, new ThresholdAscentPolicy(nArms, 10, 0.01));
      Console.WriteLine("ThresholdAscent(100,0.01) "); TestPolicyGaussianMixture(globalRand, nArms, new ThresholdAscentPolicy(nArms, 100, 0.01));
      Console.WriteLine("ThresholdAscent(1000,0.01)"); TestPolicyGaussianMixture(globalRand, nArms, new ThresholdAscentPolicy(nArms, 1000, 0.01));
      Console.WriteLine("ThresholdAscent(10000,0.01)"); TestPolicyGaussianMixture(globalRand, nArms, new ThresholdAscentPolicy(nArms, 10000, 0.01));
       */
    }


    private void TestPolicyBernoulli(Random globalRand, int nArms, IPolicy policy) {
      TestPolicy(globalRand, nArms, policy, (banditRandom, nActions) => new BernoulliBandit(banditRandom, nActions));
    }
    private void TestPolicyNormal(Random globalRand, int nArms, IPolicy policy) {
      TestPolicy(globalRand, nArms, policy, (banditRandom, nActions) => new TruncatedNormalBandit(banditRandom, nActions));
    }
    private void TestPolicyGaussianMixture(Random globalRand, int nArms, IPolicy policy) {
      TestPolicy(globalRand, nArms, policy, (banditRandom, nActions) => new GaussianMixtureBandit(banditRandom, nActions));
    }


    private void TestPolicy(Random globalRand, int nArms, IPolicy policy, Func<Random, int, IBandit> banditFactory) {
      var maxIt = 1E5;
      var reps = 30; // independent runs
      var regretForIteration = new Dictionary<int, List<double>>();
      var numberOfPullsOfSuboptimalArmsForExp = new Dictionary<int, double>();
      var numberOfPullsOfSuboptimalArmsForMax = new Dictionary<int, double>();
      // calculate statistics
      for (int r = 0; r < reps; r++) {
        var nextLogStep = 1;
        var b = banditFactory(new Random(globalRand.Next()), nArms);
        policy.Reset();
        var totalRegret = 0.0;
        var totalPullsOfSuboptimalArmsExp = 0.0;
        var totalPullsOfSuboptimalArmsMax = 0.0;
        for (int i = 0; i <= maxIt; i++) {
          var selectedAction = policy.SelectAction();
          var reward = b.Pull(selectedAction);
          policy.UpdateReward(selectedAction, reward);

          // collect stats
          if (selectedAction != b.OptimalExpectedRewardArm) totalPullsOfSuboptimalArmsExp++;
          if (selectedAction != b.OptimalMaximalRewardArm) totalPullsOfSuboptimalArmsMax++;
          totalRegret += b.OptimalExpectedReward - reward;

          if (i == nextLogStep) {
            nextLogStep *= 2;
            if (!regretForIteration.ContainsKey(i)) {
              regretForIteration.Add(i, new List<double>());
            }
            regretForIteration[i].Add(totalRegret / i);

            if (!numberOfPullsOfSuboptimalArmsForExp.ContainsKey(i)) {
              numberOfPullsOfSuboptimalArmsForExp.Add(i, 0.0);
            }
            numberOfPullsOfSuboptimalArmsForExp[i] += totalPullsOfSuboptimalArmsExp;

            if (!numberOfPullsOfSuboptimalArmsForMax.ContainsKey(i)) {
              numberOfPullsOfSuboptimalArmsForMax.Add(i, 0.0);
            }
            numberOfPullsOfSuboptimalArmsForMax[i] += totalPullsOfSuboptimalArmsMax;
          }
        }
      }
      // print
      foreach (var p in regretForIteration.Keys.OrderBy(k => k)) {
        Console.WriteLine("iter {0,8} regret avg {1,7:F5} min {2,7:F5} max {3,7:F5} suboptimal pulls (exp) {4,7:F2} suboptimal pulls (max) {5,7:F2}",
          p,
          regretForIteration[p].Average(),
          regretForIteration[p].Min(),
          regretForIteration[p].Max(),
          numberOfPullsOfSuboptimalArmsForExp[p] / (double)reps,
          numberOfPullsOfSuboptimalArmsForMax[p] / (double)reps
          );
      }
    }

  }
}