source: branches/HeuristicLab.Problems.GrammaticalOptimization-gkr/HeuristicLab.Algorithms.Bandits/ActionInfos/BernoulliPolicyActionInfo.cs @ 12893

using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using HeuristicLab.Common;

namespace HeuristicLab.Algorithms.Bandits.BanditPolicies {
  public class BernoulliPolicyActionInfo : IBanditPolicyActionInfo {
    public int NumSuccess { get; private set; }
    public int NumFailure { get; private set; }
    public int Tries { get { return NumSuccess + NumFailure; } }
    public double MaxReward { get; private set; }
    public double Value {
      get {
        return NumSuccess / (double)(Tries);
      }
    }
    public void UpdateReward(double reward) {
      //Debug.Assert(reward.IsAlmost(0.0) || reward.IsAlmost(1.0));

      //if (reward.IsAlmost(1.0)) NumSuccess++;
      MaxReward = Math.Max(MaxReward, reward);
      if (reward > 0) NumSuccess++;
      else NumFailure++;
    }
    public void Reset() {
      NumSuccess = 0;
      NumFailure = 0;
      MaxReward = double.NegativeInfinity;

    }
    public void PrintStats() {
      Console.WriteLine("expected value {0,5:F2}", Value);
    }
  }
}