// situationに合うものをPopulationから取り、足りないときはCovering
protected override void Covering( State S, Population P )
{
while( this.CList.Count == 0 )
{
// situationにあうものをPopulationから探す
this.CList = P.MatchSituation( S );
// Actionの種類
List<char> Actions = new List<char>();
int NumberOfActions = 0;
// Multiplexer(2進数)
if( Configuration.Type == "Binary" )
{
Actions.Add( '0' );
Actions.Add( '1' );
foreach( Classifier C in this.CList )
{
Actions.Remove( C.A );
}
NumberOfActions = 2 - Actions.Count;
}
// MatchSetにある行動が少ないとき
if( NumberOfActions < Configuration.Theta_mna )
{
// 一部を変化させたCondition
State state = new BinaryState( S );
state.Covering();
Classifier CC;
if( Configuration.ASName == "CS" || Configuration.ASName == "MaxCS" || Configuration.ASName == "Max" || Configuration.ASName == "Updatee0CS" )
{
CC = new SigmaNormalClassifier( state, Actions, Configuration.ExpThreshold );
}
else
{
CC = new NormalClassifier( state, Actions );
}
P.Add( CC );
// 整理
P.Delete();
this.CList = new List<Classifier>();
}
}
}
public NormalMatchSet( State S, Population P )
{
this.CList = new List<Classifier>();
this.Covering( S, P );
}
// 包摂
protected override void Subsumption( Population Pop )
{
Classifier Cl = null;
foreach( Classifier C in this.CList )
{
if( C.CouldSubsume() )
{
if( ( Cl == null ) || ( C.C.NumberOfSharp > Cl.C.NumberOfSharp ) || ( ( C.C.NumberOfSharp == Cl.C.NumberOfSharp ) && ( Configuration.MT.NextDouble() < 0.5 ) ) )
{
Cl = C;//actionsetなかに最も一般的な分類子をClにする
}
}
}
if( Cl != null )
{
// 削除中にforeachできない
List<Classifier> CL = new List<Classifier>();
foreach( Classifier C in this.CList )
{
if( Cl.IsMoreGeneral( C ) )
{
SigmaNormalClassifier Snc_ko = (SigmaNormalClassifier)C;
SigmaNormalClassifier Snc_oya = (SigmaNormalClassifier)Cl;
//10の数字は適当 可変にするか？ 1/10にする 10－7 あんまり変わらない
if (Cl.Kappa == 1 && Math.Abs(Cl.Epsilon - C.Epsilon) < 10 && Snc_ko.IsConvergenceEpsilon()
&& Snc_oya.IsConvergenceEpsilon())//subsumption するやつの分散が小さい かつε収束時だけ subsumption
{
Cl.N += C.N;
// 削除Classifier登録
CL.Add(C);
}
}
}
foreach( Classifier C in CL )
{
SigmaNormalClassifier SNC = ( SigmaNormalClassifier )Cl;
//Configuration.ESW.WriteLine( Configuration.T + "," + C.Exp + "," + Cl.C.state + "," + SNC.Epsilon_0 + "," + SNC.Epsilon + "," + SNC.Exp );
//if( C.C.state == "000###" | C.C.state == "001###" | C.C.state == "01#0##" | C.C.state == "01#1##" | C.C.state == "10##0#" | C.C.state == "10##1#" | C.C.state == "11###0" | C.C.state == "11###1" )
// Configuration.ESW.WriteLine(Configuration.T + "," + Cl.C.state + "," + C.C.state + "," + Cl.Exp + "," + Cl.Epsilon + "," + Cl.Epsilon_0 + "," + C.Exp + "," + C.Epsilon + "," + C.Epsilon_0 + "," + ++Configuration.Count);
//this.Remove( C );
//Pop.Remove( C ); 9-7 chou subsumption した分類子見たい
if (C.C.state == "1000##" | C.C.state == "0100##" | C.C.state == "0010##" | C.C.state == "0001##"
| C.C.state == "1100##" | C.C.state == "0011##" | C.C.state == "1#00##" | C.C.state == "#100##"
| C.C.state == "001###" | C.C.state == "00#1##"|C.C.state=="1000##"|C.C.state=="0100##"|C.C.state=="0010##"
|C.C.state=="00#1##")
{
Configuration.ESW.WriteLine(Configuration.T + "," + Cl.C.state + "," +Cl.A+","+ C.C.state + ","+C.A+"," + Cl.Exp + "," + Cl.Epsilon + "," + Cl.Epsilon_0 + "," + C.Exp + "," + C.Epsilon + "," + C.Epsilon_0 + "," + ++Configuration.Count);
}
//if (C.C.state == "1#00##")
//{
// SigmaNormalClassifier Snc = (SigmaNormalClassifier)C;
// Configuration.Problem_1_00.WriteLine(Configuration.T + "," + Snc.C.state + "," + C.F + "," + C.Kappa + ","
// + C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (Snc.IsConvergenceEpsilon() ? 1 : 0));
//}
this.Remove(C);
Pop.Remove(C);
}
}
}
public override void RunGA( State Situation, Population P )
{
double NumerositySum = 0.0;
double TimeStampSum = 0.0;
foreach( Classifier C in this.CList )
{
NumerositySum += C.N;
TimeStampSum += C.Ts * C.N;
}
if( Configuration.T - TimeStampSum / NumerositySum > Configuration.Theta_GA )
{
foreach( Classifier C in this.CList )
{
C.Ts = Configuration.T;
}
Classifier Parent_1 = this.SelectOffspring();
Classifier Parent_2 = this.SelectOffspring();
Classifier Child_1 = new SigmaNormalClassifier( ( SigmaNormalClassifier )Parent_1 );
Classifier Child_2 = new SigmaNormalClassifier( ( SigmaNormalClassifier )Parent_2 );
///nakata added
Child_1.F /= Child_1.N;
Child_2.F /= Child_2.N;
//////////////
Child_1.N = Child_2.N = 1;
Child_1.Exp = Child_2.Exp = 0;
Child_1.St = Child_2.St = 0;
Child_1.M = Child_2.M = 0;
Child_1.S = Child_2.S = 0;
//Child_1.Epsilon_0 = Child_2.Epsilon_0 = Configuration.Epsilon_0;
SigmaNormalClassifier SNP1 = ( SigmaNormalClassifier )Parent_1;
SigmaNormalClassifier SNP2 = ( SigmaNormalClassifier )Parent_2;
SigmaNormalClassifier SNC1 = ( SigmaNormalClassifier )Child_1;
SigmaNormalClassifier SNC2 = ( SigmaNormalClassifier )Child_2;
// 交叉
if( Configuration.MT.NextDouble() < Configuration.Chai )
{
Child_1.Crossover( Child_2 );
Child_1.P = ( Parent_1.P + Parent_2.P ) / 2;
//Child_1.Epsilon = Parent_1.Epsilon + Parent_2.Epsilon;
Child_1.Epsilon = ( Parent_1.Epsilon + Parent_2.Epsilon ) / 2;
Child_1.F = ( Parent_1.F + Parent_2.F ) / 2;
//Child_1.M = ( Parent_1.M + Parent_2.M ) / 2;
//Child_1.S = ( Parent_1.S + Parent_2.S ) / 2;
Child_1.Epsilon_0 = ( Parent_1.Epsilon_0 + Parent_2.Epsilon_0 ) / 2;
//Child_1.Epsilon_0 = Math.Min(Parent_1.Epsilon_0, Parent_2.Epsilon_0);
Child_2.P = Child_1.P;
Child_2.Epsilon = Child_1.Epsilon;
Child_2.F = Child_1.F;
//Child_2.M = Child_1.M;
//Child_2.S = Child_1.S;
Child_2.Epsilon_0 = Child_1.Epsilon_0;
for( int i = 0; i < SNC1.WinningRate.Count(); i++ )
{
SNC1.WinningRate[i] = SNC2.WinningRate[i] = ( SNP1.WinningRate[i] + SNP2.WinningRate[i] ) / 2;
}
}
Child_1.F *= 0.1;
Child_2.F *= 0.1;
for( int i = 0; i < SNC1.WinningRate.Count(); i++ )
{
SNC1.WinningRate[i] *= 0.1;
SNC2.WinningRate[i] *= 0.1;
}
// bothChild
Child_1.Mutation( Situation );
Child_2.Mutation( Situation );
if( Configuration.DoGASubsumption )
{
if( Parent_1.DoesSubsume( Child_1 ) )
{
Parent_1.N++;
}
else if( Parent_2.DoesSubsume( Child_1 ) )
{
Parent_2.N++;
}
else
{
P.Insert( Child_1 );
}
P.Delete();
if( Parent_1.DoesSubsume( Child_2 ) )
{
Parent_1.N++;
}
else if( Parent_2.DoesSubsume( Child_2 ) )
{
Parent_2.N++;
}
else
{
P.Insert( Child_2 );
}
P.Delete();
}
else
{
P.Insert( Child_1 );
P.Delete();
P.Insert( Child_2 );
P.Delete();
}
}
}
public override void Update( Population Pop, double P, StdList Sigma )
{
double SumNumerosity = 0;
foreach( Classifier C in this.CList )
{
SumNumerosity += C.N;
}
//if( Configuration.URE_Epsilon0 != Configuration.Rho )
//{
// Configuration.URE_Epsilon0 += Configuration.Epsilon_0 * 5;
// foreach( Classifier C in this.CList )
// {
// C.Epsilon_0 += Configuration.Beta * ( Configuration.URE_Epsilon0 - C.Epsilon_0 );
// }
//}
//else
//{
//if( SNC.IsConvergenceEpsilon() && Sigma.IsConvergenceSigma() )
//{
// foreach( Classifier C in this.CList )
// {
// }
//}
//}
foreach( Classifier C in this.CList )
{
C.Exp++;
if( C.Exp < 1 /Configuration.Beta )
{
C.P += ( P - C.P ) / C.Exp;
}
else
{
C.P += Configuration.Beta * ( P - C.P );
}
//if( C.Exp < Configuration.Beta ) // 9-23 張 ここscript は exp < 1/beta
if (C.Exp < Configuration.Beta)
{
C.As += ( SumNumerosity - C.As ) / C.Exp;
}
else
{
C.As += Configuration.Beta * ( SumNumerosity - C.As );
}
if( C.C.state == "11###0" && C.A == '1' )
{
//Configuration.ESW.WriteLine( Configuration.T + "," + C.F + "," + C.Kappa + "," + C.Epsilon_0 + "," + C.Epsilon + "," + C.Exp + "," + Math.Sqrt( C.S / ( C.St - 1 ) ) );
//Console.WriteLine( Configuration.T + " " + C.Exp );
}
// 標準偏差計算
C.St++;
double X = P - C.M;
C.M += X / C.St;
C.S += ( C.St - 1 ) * X * X / C.St;
if( C.GetType().Name == "SigmaNormalClassifier" )
{
// このIterationまでのepsilonを記録ずらし
SigmaNormalClassifier SNC = ( SigmaNormalClassifier )C;
for( int index = SNC.EpsilonList.Count() - 1; index > 0; index-- )
{
SNC.EpsilonList[index] = SNC.EpsilonList[index - 1];
}
SNC.EpsilonList[0] = Math.Sqrt(C.S / (C.St - 1));
//bool StateFlag = true;
//foreach(StdList SL in Configuration.Stdlist)
//{
// // 分類子に含まれるstate
// //if(SL.IsIncluded(SNC.C.state, SNC.A))
// //{
// // 一つでも収束していなければ
// if(!SL.IsConvergenceSigma())
// {
// StateFlag = false;
// }
// //}
//}
//if( SNC.IsConvergenceEpsilon() )
//if( SNC.IsConvergenceEpsilon() && StateFlag )
if( Sigma.IsConvergenceSigma() )
{
double sigma_a=0;
double sigma_b=0;
//9-24 張 1#00 算出する時用のもの追加
if(C.C.state=="1#00##")
{
//1100 と 1000 のsigma で1#00を更新
foreach(StdList SL in Configuration.Stdlist)
{
if(SL.C=="110000"){ sigma_a =SL.S;}
if(SL.C=="100000"){ sigma_b =SL.S;}
}
//sigma はvariancetableから
C.Epsilon_0 += Configuration.Beta * (Math.Sqrt(sigma_a*sigma_a +sigma_b*sigma_b) + Configuration.Epsilon_0 - C.Epsilon_0);
}
if (C.C.state == "#100##")
{
//1100 と 1000 のsigma で1#00を更新
foreach (StdList SL in Configuration.Stdlist)
{
if (SL.C == "110000") { sigma_a = SL.S; }
if (SL.C == "010000") { sigma_b = SL.S; }
}
//sigma はvariancetableから
C.Epsilon_0 += Configuration.Beta * (Math.Sqrt(sigma_a * sigma_a + sigma_b * sigma_b) + Configuration.Epsilon_0 - C.Epsilon_0);
}
if (C.C.state == "001###")
{
//1100 と 1000 のsigma で1#00を更新
foreach (StdList SL in Configuration.Stdlist)
{
if (SL.C == "001100") { sigma_a = SL.S; }
if (SL.C == "001000") { sigma_b = SL.S; }
}
//sigma はvariancetableから
C.Epsilon_0 += Configuration.Beta * (Math.Sqrt(sigma_a * sigma_a + sigma_b * sigma_b) + Configuration.Epsilon_0 - C.Epsilon_0);
}
if (C.C.state == "00#1##")
{
//1100 と 1000 のsigma で1#00を更新
foreach (StdList SL in Configuration.Stdlist)
{
if (SL.C == "001100") { sigma_a = SL.S; }
if (SL.C == "000100") { sigma_b = SL.S; }
}
//sigma はvariancetableから
C.Epsilon_0 += Configuration.Beta * (Math.Sqrt(sigma_a * sigma_a + sigma_b * sigma_b) + Configuration.Epsilon_0 - C.Epsilon_0);
}
else
{
C.Epsilon_0 += Configuration.Beta * ( Sigma.S + Configuration.Epsilon_0 - C.Epsilon_0 );
}
}
if( SNC.IsConvergenceEpsilon() )
//if( SNC.IsConvergenceEpsilon() && StateFlag )
//if(SNC.Exp > 1)
//if(SNC.IsConvergenceEpsilon() && Sigma.IsConvergenceSigma())
{
Configuration.FlagSigma = true;
SNC.Epsilon = SNC.EpsilonList[0];
//SNC.Epsilon += Configuration.Beta * ( SNC.EpsilonList[0] - SNC.Epsilon );
//if( C.Exp < Configuration.Beta )
//{
// C.Epsilon += ( Math.Abs( P - C.P ) - C.Epsilon ) / C.Exp;
//}
//else
//{
// C.Epsilon += Configuration.Beta * ( Math.Abs( P - C.P ) - C.Epsilon );
//}
//C.Epsilon_0 += Configuration.Beta * ( Sigma.S + Configuration.Epsilon_0 - C.Epsilon_0 );
//C.Epsilon_0 = Sigma.S + Configuration.Epsilon_0;
//C.Epsilon_0 = Sigma.S;
}
else
{
//if (C.Exp < Configuration.Beta)//9-23 張 ここscript は exp<Beta
if (C.Exp < Configuration.Beta)
{
C.Epsilon += ( Math.Abs( P - C.P ) - C.Epsilon ) / C.Exp;
}
else
{
C.Epsilon += Configuration.Beta * ( Math.Abs( P - C.P ) - C.Epsilon );
}
}
}
else //SigmaNormalClassifier ではない場合
{
//if( C.Exp < Configuration.Beta )//9-23 張 ここscript は exp<Beta
if (C.Exp < Configuration.Beta)
{
C.Epsilon += ( Math.Abs( P - C.P ) - C.Epsilon ) / C.Exp;
}
else
{
C.Epsilon += Configuration.Beta * ( Math.Abs( P - C.P ) - C.Epsilon );
}
}
//if(C.St > 250)
//{
//C.Epsilon_0 += Configuration.Beta * (Configuration.Epsilon_0 + Math.Sqrt( C.S / ( C.St - 1 ) ) - C.Epsilon_0);
//Console.WriteLine(C.Epsilon_0);
//Console.WriteLine("st" + C.St);
//}
//if( Configuration.T > 5000 )
//if(Configuration.IsConvergenceSigma())
}
this.UpdateFitness();
if( Configuration.DoActionSetSubsumption )
{
this.Subsumption( Pop );
}
}
/// <summary> /// Subsumpiton /// </summary> /// <param name="Pop">Population</param> protected abstract void Subsumption( Population Pop );
/// <summary> /// Fitness更新 /// </summary> /// <param name="Pop">Population</param> /// <param name="P">報酬の値</param> public abstract void Update( Population Pop, double P, StdList Sigma );
protected override void Subsumption( Population Pop )
{
Classifier Cl = null;
foreach( Classifier C in this.CList )
{
if( C.CouldSubsume() )
{
if( ( Cl == null ) || ( C.C.NumberOfSharp > Cl.C.NumberOfSharp ) || ( ( C.C.NumberOfSharp == Cl.C.NumberOfSharp ) && ( Configuration.MT.NextDouble() < 0.5 ) ) )
{
Cl = C;
}
}
}
if( Cl != null )
{
// 削除中にforeachできない
List<Classifier> CL = new List<Classifier>();
foreach( Classifier C in this.CList )
{
if( Cl.IsMoreGeneral( C ) )
{
Cl.N += C.N;
// 削除Classifier登録
CL.Add( C );
}
}
foreach( Classifier C in CL )
{
if(C.C.state=="1#00##")
{
SigmaNormalClassifier SNC = (SigmaNormalClassifier)C;
Configuration.Problem_1_00.WriteLine(Configuration.T + "," + SNC.C.state + "," + C.F + "," + C.Kappa + ","
+ C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (SNC.IsConvergenceEpsilon() ? 1 : 0));
}
this.Remove( C );
Pop.Remove( C );
}
}
}
// situationに合うものをPopulationから取り、足りないときはCovering
protected override void Covering( State S, Population P )
{
}
public NotCoveringMatchSet( State S, Population P )
{
this.CList = new List<Classifier>();
this.CList = P.MatchSituation( S );
}
/// <summary>
/// 評価
/// </summary>
/// <param name="Env">環境</param>
/// <param name="P">Population</param>
/// <returns>performance</returns>
public static double Exploit( Population P )
{
// situation取得
State S = Configuration.ExploitEnv.GetState();
// Matchset生成
MatchSet M = new NotCoveringMatchSet( S, P );
// PredictionArray生成
PredictionArray PA = new GreedyPredictionArray( M );
// Action決定
char Action = PA.SelectAction();
// 報酬獲得
double Rho = Configuration.ExploitEnv.ActionExploit( Action );
//if( Rho == 0 && Configuration.T > 35530 )
//{
// Console.WriteLine( Configuration.T + " : " + S.state + " : " + Action + " : " + Rho );
// foreach(double d in PA.PA)
// {
// Console.WriteLine(d);
// }
// System.Threading.Thread.Sleep( 1000 );
//}
if(Action == '0')
{
Configuration.ZeroList.Add( Rho );
}
else if(Action == '1')
{
Configuration.OneList.Add( Rho );
}
return Rho;
}
public static void Experiment( Environment Env, Population P )
{
// 変数初期化
Configuration.T = 0;
ActionSet PreviousAS = null;
double PreviousRho = 0;
State PreviousS = null;
// stdlist収束
bool ConvergenceStelist = false;
// 移動平均計算用
double[] RhoArray = new double[Configuration.Iteration];
int[] Num = new int[Configuration.Iteration];
//double[] Std = new double[Configuration.Iteration];
Configuration.ZeroList = new List<double>();
Configuration.OneList = new List<double>();
// 提案手法 Condition毎の分散
Configuration.Stdlist = new StdList[( int )Math.Pow( 2, Configuration.L ) * 2];
for( int i = 0; i < ( int )Math.Pow( 2, Configuration.L ); i++ )
{
Configuration.Stdlist[i * 2] = new StdList( i, '0' );
Configuration.Stdlist[i * 2 + 1] = new StdList( i, '1' );
}
//StreamWriter LD = new StreamWriter( "./LearningData_" + Configuration.Seed + "CnoiseWidth_" + Configuration.NoiseWidth
// + "AS_" + Configuration.ASName + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
// + "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
//LD.WriteLine( "T,state,Action,Rho,ActionExploit" );
// 実験1a ノイズを既知のものとして扱う
if(Configuration.ASName == "WellKnown")
{
Configuration.Epsilon_0 += Configuration.NoiseWidth;
}
// メインループ
#region main roop
while ( Configuration.T < Configuration.Iteration )
{
if (Configuration.T == 40269) {
Console.WriteLine("stoped");
Console.ReadLine(); }
//Console.WriteLine( Configuration.T + " : " + P.CountNumerosity() + " : " + P.CList.Count() );
// situation取得
State S = Env.GetState();
// MatchSet生成
MatchSet M = new NormalMatchSet( S, P );
// PredictionArray取得
PredictionArray PA = new EpsilonGreedyPredictionArray( M );
// Action決定
char Action = PA.SelectAction();
// ActionSet選択
ActionSet AS;
if( Configuration.ASName == "CS" )
{
AS = new ConditionSigmaActionSet( M.MatchAction( Action ) );
}
//else if( Configuration.ASName == "MaxCS" || Configuration.ASName == "Max" )
//{
// AS = new MaxConditionSigmaActionSet( M.MatchAction( Action ) );
//}
else if( Configuration.ASName == "WellKnown" ) // 実験1a
{
AS = new NormalActionSet( M.MatchAction( Action ) );
}
else if( Configuration.ASName == "Updatee0CS" ) // 実験1b
{
AS = new UpdateEpsilon_0_ConditionSigmaActionSet( M.MatchAction( Action ) );
}
else if(Configuration.ASName == "Tornament")
{
AS = new TornamentSelectionActionSet( M.MatchAction( Action ) );
}
else
{
AS = new NormalActionSet( M.MatchAction( Action ) );
}
// EnvにActionし、報酬獲得
double Rho = Env.ExecuteAction(Action);
//if ( == "1#00##" )
//{
// Configuration.Problem.WriteLine(S.state + "," + Action + "," + Configuration.T + "," + Rho);
//}
StdList Sigma = null;
// 提案手法 分散の計算
foreach( StdList SL in Configuration.Stdlist )
{
if( ( SL.C == S.state ) && ( SL.A == Action ) )
{
// situationの分散取得
SL.Update( Rho );
Sigma = SL;
}
}
// 提案手法(中田)
if( Configuration.ASName == "CS" )
{
Configuration.URE_Epsilon0 = -1;
// 最小値
double d = Configuration.Rho;
foreach( SigmaNormalClassifier C in AS.CList )
{
if( d > C.S && C.IsConvergenceEpsilon() )
{
d = Math.Sqrt( C.S / ( C.St - 1 ) );
}
}
Configuration.URE_Epsilon0 = d;
}
//if (Configuration.T > 18936&&Configuration.T<18938)
//{
// foreach (Classifier C in AS.CList)
// {
// if (C.C.state == "1#00##" )
// {
// Console.WriteLine(Configuration.T + " : " + S.state + " : " + Action + " : " + Rho + " : " + C.Exp);
// }
// }
//}
// 学習データ記録
//LD.WriteLine( Configuration.T + "," + S.state + "," + Action + "," + Rho + "," + Env.ActionExploit( Action ) );
// マルチステップ問題
if( PreviousAS != null )
{
double p = PreviousRho + Configuration.Gamma * PA.MAX();
PreviousAS.Update( P, p, Sigma );
PreviousAS.RunGA( PreviousS, P ); //komine
}
// マルチステップ問題の終着またはシングルステップ問題
if( Env.Eop )
{
double p = Rho;
AS.Update( P, p, Sigma );
AS.RunGA( S, P );//komine
PreviousAS = null;
}
else
{
PreviousAS = AS;
PreviousRho = Rho;
PreviousS = S;
}
//if(Configuration.ASName == "CS")
//{
// SigmaNormalPopulation SP = ( SigmaNormalPopulation )P;
// SP.RoundRobin();
//}
// accuracyが一定以上のfitnessの平均値
//double SumFitness = 0;
//int NumberOfClassifiers = 0;
//foreach( Classifier C in P.CList )
//{
// //SumFitness += C.F;
// //NumberOfClassifiers++;
// if( C.C.state == "11####" && C.A == '0' )
// Configuration.ESW.WriteLine( Configuration.T + "," + C.Epsilon );
//}
foreach(StdList C in Configuration.Stdlist)
{
//if( C.C == "111111" && C.A == '0' )
//Configuration.ESW.WriteLine( Configuration.T + "," + C.S );
}
//Configuration.ESW.WriteLine( Configuration.T + "," + SumFitness + "," + NumberOfClassifiers + "," + SumFitness / NumberOfClassifiers);
RhoArray[Configuration.T] = Exploit( P );
//Num[Configuration.T] = P.CountNumerosity();
Num[Configuration.T] = P.CList.Count();
//Std[Configuration.T] = Math.Sqrt( Stdlist[20].Sigma / (Stdlist[20].T - 1));
if( Configuration.StartTime < 0 && Configuration.FlagSigma && Configuration.FlagEpsilon )
{
Configuration.StartTime = Configuration.T;
}
Configuration.FlagSigma = Configuration.FlagEpsilon = false;
//if( ( Configuration.T < 20001 && Configuration.T % 1000 == 0 ) || Configuration.T % 5000 == 0 )
//{
// P.Show();
//}
//if( Configuration.T % 1000 == 0 && Configuration.T < 20001 && ( Configuration.ASName == "CS" || Configuration.ASName == "MaxCS" || Configuration.ASName == "Max" || Configuration.ASName == "Updatee0CS" ) )
//{
// StreamWriter stdSw = new StreamWriter( "./VarianceTable_" + Configuration.T + "_" + Configuration.Seed + "CnoiseWidth" + Configuration.NoiseWidth
//+ "AS_" + Configuration.ASName + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
//+ "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
// stdSw.WriteLine( "condition,action,sigma,time,convergence" );
// foreach( StdList SL in Configuration.Stdlist )
// {
// stdSw.WriteLine( SL.C + "," + SL.A + "," + SL.S + "," + SL.T + "," + ( SL.IsConvergenceSigma() ? 1 : 0 ) ); // 1 : 収束
// }
// stdSw.Close();
//}
if( !ConvergenceStelist && ( Configuration.ASName == "CS" || Configuration.ASName == "MaxCS" || Configuration.ASName == "Max" || Configuration.ASName == "Updatee0CS" ) )
{
int i = 1;
foreach( StdList SL in Configuration.Stdlist )
{
i *= ( SL.IsConvergenceSigma() ? 1 : 0 );
}
if( i == 1 )
{
StreamWriter stdSw = new StreamWriter( "./ConvergenceVT_" + Configuration.T + "_" + Configuration.Seed + "CnoiseWidth" + Configuration.NoiseWidth
+ "AS_" + Configuration.ASName + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
+ "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
stdSw.WriteLine( "condition,action,sigma,time,convergence" );
foreach( StdList SL in Configuration.Stdlist )
{
stdSw.WriteLine( SL.C + "," + SL.A + "," + SL.S + "," + SL.T + "," + ( SL.IsConvergenceSigma() ? 1 : 0 ) ); // 1 : 収束
}
stdSw.Close();
ConvergenceStelist = true;
}
}
//if (Configuration.T > 14896& Configuration.T <14899)
//{
// P.Show();
// M.Show();
// AS.Show();//9-7 chou ループたびのpopulation 見たい
//}
foreach (Classifier C in P.CList)
{
if (C.GetType().Name == "SigmaNormalClassifier")
{
if (C.C.state == "1000##")
{
SigmaNormalClassifier SNC = (SigmaNormalClassifier)C;
Configuration.Problem_1000.WriteLine(Configuration.T + "," + SNC.C.state + ","+SNC.A+"," + C.F + "," + C.Kappa + ","
+ C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (SNC.IsConvergenceEpsilon() ? 1 : 0));
}
if (C.C.state == "0100##")
{
SigmaNormalClassifier SNC = (SigmaNormalClassifier)C;
Configuration.Problem_0100.WriteLine(Configuration.T + "," + SNC.C.state + ","+SNC.A +"," + C.F + "," + C.Kappa + ","
+ C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (SNC.IsConvergenceEpsilon() ? 1 : 0));
}
if (C.C.state == "0010##")
{
SigmaNormalClassifier SNC = (SigmaNormalClassifier)C;
Configuration.Problem_0010.WriteLine(Configuration.T + "," + SNC.C.state + "," + SNC.A + "," + C.F + "," + C.Kappa + ","
+ C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (SNC.IsConvergenceEpsilon() ? 1 : 0));
}
if (C.C.state == "0001##")
{
SigmaNormalClassifier SNC = (SigmaNormalClassifier)C;
Configuration.Problem_0001.WriteLine(Configuration.T + "," + SNC.C.state + "," + SNC.A + "," + C.F + "," + C.Kappa + ","
+ C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (SNC.IsConvergenceEpsilon() ? 1 : 0));
}
if (C.C.state == "1#00##")
{
SigmaNormalClassifier SNC = (SigmaNormalClassifier)C;
Configuration.Problem__100.WriteLine(Configuration.T + "," + SNC.C.state + "," + C.A + "," + C.F + "," + C.Kappa + ","
+ C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (SNC.IsConvergenceEpsilon() ? 1 : 0));
}
if (C.C.state == "#100##")
{
SigmaNormalClassifier SNC = (SigmaNormalClassifier)C;
Configuration.Problem__100.WriteLine(Configuration.T + "," + SNC.C.state + "," + C.A + "," + C.F + "," + C.Kappa + ","
+ C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (SNC.IsConvergenceEpsilon() ? 1 : 0));
}
if (C.C.state == "001###")
{
SigmaNormalClassifier SNC = (SigmaNormalClassifier)C;
Configuration.Problem__100.WriteLine(Configuration.T + "," + SNC.C.state + "," + C.A + "," + C.F + "," + C.Kappa + ","
+ C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (SNC.IsConvergenceEpsilon() ? 1 : 0));
}
if (C.C.state == "00#1##")
{
SigmaNormalClassifier SNC = (SigmaNormalClassifier)C;
Configuration.Problem__100.WriteLine(Configuration.T + "," + SNC.C.state + "," + C.A + "," + C.F + "," + C.Kappa + ","
+ C.Epsilon + "," + C.Epsilon_0 + "," + C.N + "," + (SNC.IsConvergenceEpsilon() ? 1 : 0));
}
}
}
//if (Configuration.T > 19835 && Configuration.T < 19840)
//{
// P.Show();
//}
//if (Configuration.T > 7200 && Configuration.T < 7300)
//{
// P.Show();
//}
//if (Configuration.T > 7700 && Configuration.T < 7850)
//{
// P.Show();
//}
//if (Configuration.T > 8400 && Configuration.T < 8600)
//{
// P.Show();
//}
//if (Configuration.T >11400 && Configuration.T < 11500)
//{
// P.Show();
//}
//if (Configuration.T > 14200 && Configuration.T < 14300)
//{
// P.Show();
//}
Configuration.T++;
//if (Configuration.T > 19996)
//{
// Console.Read();
//}
}
#endregion
Configuration.Problem_1_00.Close();
Configuration.Problem__100.Close();
Configuration.Problem_1000.Close();
Configuration.Problem_0100.Close();
Configuration.Problem_0010.Close();
Configuration.Problem_0001.Close();
P.Show();
if( ( Configuration.ASName == "CS" || Configuration.ASName == "MaxCS" || Configuration.ASName == "Max" || Configuration.ASName == "Updatee0CS" ) )
{
StreamWriter stdSw = new StreamWriter( "./VarianceTable_" + Configuration.T + "_" + Configuration.Seed + "CnoiseWidth" + Configuration.NoiseWidth
+ "AS_" + Configuration.ASName + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
+ "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
stdSw.WriteLine( "condition,action,sigma,time,convergence,convergencetime" );
foreach( StdList SL in Configuration.Stdlist )
{
stdSw.WriteLine( SL.C + "," + SL.A + "," + SL.S + "," + SL.T + "," + ( SL.IsConvergenceSigma() ? 1 : 0 ) + "," + SL.ConvergenceTime ); // 1 : 収束
}
stdSw.Close();
}
//LD.Close();
StreamWriter sw = new StreamWriter( "./performance_" + Configuration.Seed + "CnoiseWidth_" + Configuration.NoiseWidth
+ "AS_" + Configuration.ASName + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
+ "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
//StreamWriter sw = new StreamWriter( "./performance_" + Configuration.Seed + "CnoiseWidth_" + Configuration.NoiseWidth
// + "AS_" + "CS" + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
// + "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
sw.WriteLine( "Performance,PopulationSize," + Configuration.StartTime );
for( int i = 0; i < RhoArray.Count() - Configuration.SMA; i++ )
{
double R = 0;
double N = 0;
for( int j = 0; j < Configuration.SMA; j++ )
{
R += RhoArray[i + j];
N += Num[i + j];
}
R /= Configuration.SMA;
N /= Configuration.SMA;
sw.WriteLine( R + "," + N );
}
sw.Close();
StreamWriter Zerosw = new StreamWriter( "./Zero_per_" + Configuration.Seed + "CnoiseWidth_" + Configuration.NoiseWidth
+ "AS_" + Configuration.ASName + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
+ "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
//StreamWriter sw = new StreamWriter( "./performance_" + Configuration.Seed + "CnoiseWidth_" + Configuration.NoiseWidth
// + "AS_" + "CS" + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
// + "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
Zerosw.WriteLine( "Performance,dummy," + Configuration.StartTime );
for( int i = 0; i < Configuration.ZeroList.Count() - Configuration.SMA; i++ )
{
double R = 0;
double N = 0;
for( int j = 0; j < Configuration.SMA; j++ )
{
R += Configuration.ZeroList[i + j];
N += Num[i + j];
}
R /= Configuration.SMA;
N /= Configuration.SMA;
Zerosw.WriteLine( R + "," + N );
}
Zerosw.Close();
StreamWriter Onesw = new StreamWriter( "./One_per_" + Configuration.Seed + "CnoiseWidth_" + Configuration.NoiseWidth
+ "AS_" + Configuration.ASName + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
+ "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
//StreamWriter sw = new StreamWriter( "./performance_" + Configuration.Seed + "CnoiseWidth_" + Configuration.NoiseWidth
// + "AS_" + "CS" + "ET_" + Configuration.ExpThreshold + "DS_" + Configuration.DifferenceSigma + "LS_" + Configuration.LookBackSigma
// + "DE_" + Configuration.DifferenceEpsilon + "LE_" + Configuration.LookBackEpsilon + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
Onesw.WriteLine( "Performance,dummy," + Configuration.StartTime );
for( int i = 0; i < Configuration.OneList.Count() - Configuration.SMA; i++ )
{
double R = 0;
double N = 0;
for( int j = 0; j < Configuration.SMA; j++ )
{
R += Configuration.OneList[i + j];
N += Num[i + j];
}
R /= Configuration.SMA;
N /= Configuration.SMA;
Onesw.WriteLine( R + "," + N );
}
Onesw.Close();
foreach( StdList SL in Configuration.Stdlist )
{
//Console.WriteLine( SL.C + " " + SL.A + " " + SL.T + " " + SL.M + " " + SL.S );
}
//StreamWriter sow = new StreamWriter( "./sigma_" + Configuration.Seed + "CnoiseWidth_" + Configuration.NoiseWidth + "e0_" + Configuration.Epsilon_0 + ".csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
//foreach( double d in Std )
//{
// sow.WriteLine( d );
//}
//sow.Close();
Configuration.ESW.Close();
//Configuration.Problem.Close();
System.IO.Directory.SetCurrentDirectory( "../");
StreamWriter swP = new StreamWriter( "PPP.csv", true, System.Text.Encoding.GetEncoding( "shift_jis" ) );
swP.WriteLine( Configuration.NoiseWidth + "," + Configuration.ASName + "," + P.CList.Count() );
swP.Close();
}
// 包摂
protected override void Subsumption( Population Pop )
{
Classifier Cl = null;
foreach( Classifier C in this.CList )
{
if( C.CouldSubsume() )
{
if( ( Cl == null ) || ( C.C.NumberOfSharp > Cl.C.NumberOfSharp ) || ( ( C.C.NumberOfSharp == Cl.C.NumberOfSharp ) && ( Configuration.MT.NextDouble() < 0.5 ) ) )
{
Cl = C;
}
}
}
if( Cl != null )
{
// 削除中にforeachできない
List<Classifier> CL = new List<Classifier>();
foreach( Classifier C in this.CList )
{
if( Cl.IsMoreGeneral( C ) )
{
Cl.N += C.N;
// 削除Classifier登録
CL.Add( C );
}
}
foreach( Classifier C in CL )
{
this.Remove( C );
Pop.Remove( C );
}
}
}
public override void Update( Population Pop, double P, StdList Sigma )
{
double SumNumerosity = 0;
foreach( Classifier C in this.CList )
{
SumNumerosity += C.N;
}
//if( Configuration.URE_Epsilon0 != Configuration.Rho )
//{
// Configuration.URE_Epsilon0 += Configuration.Epsilon_0 * 5;
// foreach( Classifier C in this.CList )
// {
// C.Epsilon_0 += Configuration.Beta * ( Configuration.URE_Epsilon0 - C.Epsilon_0 );
// }
//}
//else
//{
//if( SNC.IsConvergenceEpsilon() && Sigma.IsConvergenceSigma() )
//{
// foreach( Classifier C in this.CList )
// {
// }
//}
//}
foreach( Classifier C in this.CList )
{
C.Exp++;
if( C.Exp < 1 / Configuration.Beta )
{
C.P += ( P - C.P ) / C.Exp;
}
else
{
C.P += Configuration.Beta * ( P - C.P );
}
if( C.Exp < Configuration.Beta )
{
C.As += ( SumNumerosity - C.As ) / C.Exp;
}
else
{
C.As += Configuration.Beta * ( SumNumerosity - C.As );
}
//if( C.C.state == "0000#######" && C.A == '0' )
//{
// Configuration.ESW.WriteLine( Configuration.T + "," + C.F + "," + C.Kappa + "," + C.Epsilon_0 + "," + C.Epsilon + "," + C.Exp + "," + Math.Sqrt( C.S / ( C.St - 1 ) ) );
// Console.WriteLine( Configuration.T + " " + C.Exp );
//}
//if( C.C.state == "10##0#" && C.A == '0' )
//{
// Configuration.ESW.WriteLine( Configuration.T + "," + C.F + "," + C.Kappa + "," + C.Epsilon_0 + "," + C.Epsilon + "," + C.Exp + "," + Math.Sqrt( C.S / ( C.St - 1 ) ) );
// //Console.WriteLine( Configuration.T + " " + this.Exp );
//}
// 標準偏差計算
C.St++;
double X = P - C.M;
C.M += X / C.St;
C.S += ( C.St - 1 ) * X * X / C.St;
if( C.GetType().Name == "SigmaNormalClassifier" )
{
// このIterationまでのepsilonを記録ずらし
SigmaNormalClassifier SNC = ( SigmaNormalClassifier )C;
for( int index = SNC.EpsilonList.Count() - 1; index > 0; index-- )
{
SNC.EpsilonList[index] = SNC.EpsilonList[index - 1];
}
SNC.EpsilonList[0] = Math.Sqrt( C.S / ( C.St - 1 ) );
//bool StateFlag = true;
//foreach(StdList SL in Configuration.Stdlist)
//{
// // 分類子に含まれるstate
// //if(SL.IsIncluded(SNC.C.state, SNC.A))
// //{
// // 一つでも収束していなければ
// if(!SL.IsConvergenceSigma())
// {
// StateFlag = false;
// }
// //}
//}
//if( SNC.IsConvergenceEpsilon() )
//if( SNC.IsConvergenceEpsilon() && StateFlag )
if( Sigma.IsConvergenceSigma() )
{
C.Epsilon_0 += Configuration.Beta * ( Sigma.S + Configuration.Epsilon_0 - C.Epsilon_0 );
}
if( C.Exp < Configuration.Beta )
{
C.Epsilon += ( Math.Abs( P - C.P ) - C.Epsilon ) / C.Exp;
}
else
{
C.Epsilon += Configuration.Beta * ( Math.Abs( P - C.P ) - C.Epsilon );
}
}
else
{
if( C.Exp < Configuration.Beta )
{
C.Epsilon += ( Math.Abs( P - C.P ) - C.Epsilon ) / C.Exp;
}
else
{
C.Epsilon += Configuration.Beta * ( Math.Abs( P - C.P ) - C.Epsilon );
}
}
//if(C.St > 250)
//{
//C.Epsilon_0 += Configuration.Beta * (Configuration.Epsilon_0 + Math.Sqrt( C.S / ( C.St - 1 ) ) - C.Epsilon_0);
//Console.WriteLine(C.Epsilon_0);
//Console.WriteLine("st" + C.St);
//}
//if( Configuration.T > 5000 )
//if(Configuration.IsConvergenceSigma())
}
this.UpdateFitness();
if( Configuration.DoActionSetSubsumption )
{
this.Subsumption( Pop );
}
}
public override void RunGA( State Situation, Population P )
{
double NumerositySum = 0.0;
double TimeStampSum = 0.0;
foreach( Classifier C in this.CList )
{
NumerositySum += C.N;
TimeStampSum += C.Ts * C.N;
}
if( Configuration.T - TimeStampSum / NumerositySum > Configuration.Theta_GA )
{
foreach( Classifier C in this.CList )
{
C.Ts = Configuration.T;
}
Classifier Parent_1 = this.SelectOffspring();
Classifier Parent_2 = this.SelectOffspring();
Classifier Child_1 = new NormalClassifier( ( NormalClassifier )Parent_1 );
Classifier Child_2 = new NormalClassifier( ( NormalClassifier )Parent_2 );
Child_1.N = Child_2.N = 1;
Child_1.Exp = Child_2.Exp = 0;
Child_1.St = Child_2.St = 0;
Child_1.M = Child_2.M = 0;
Child_1.S = Child_2.S = 0;
if( Configuration.MT.NextDouble() < Configuration.Chai )
{
Child_1.Crossover( Child_2 );
Child_1.P = ( Parent_1.P + Parent_2.P ) / 2;
Child_1.Epsilon = ( Parent_1.Epsilon + Parent_2.Epsilon ) / 2;
Child_1.F = ( Parent_1.F + Parent_2.F ) / 2;
//Child_1.M = ( Parent_1.M + Parent_2.M ) / 2;
//Child_1.S = ( Parent_1.S + Parent_2.S ) / 2;
Child_2.P = Child_1.P;
Child_2.Epsilon = Child_1.Epsilon;
Child_2.F = Child_1.F;
//Child_2.M = Child_1.M;
//Child_2.S = Child_1.S;
}
Child_1.F *= 0.1;
Child_2.F *= 0.1;
// bothChild
Child_1.Mutation( Situation );
Child_2.Mutation( Situation );
if( Configuration.DoGASubsumption )
{
if( Parent_1.DoesSubsume( Child_1 ) )
{
Parent_1.N++;
}
else if( Parent_2.DoesSubsume( Child_1 ) )
{
Parent_2.N++;
}
else
{
P.Insert( Child_1 );
}
P.Delete();
if( Parent_1.DoesSubsume( Child_2 ) )
{
Parent_1.N++;
}
else if( Parent_2.DoesSubsume( Child_2 ) )
{
Parent_2.N++;
}
else
{
P.Insert( Child_2 );
}
P.Delete();
}
else
{
P.Insert( Child_1 );
P.Delete();
P.Insert( Child_2 );
P.Delete();
}
}
}
/// <summary> /// GA /// </summary> /// <param name="Situation">situation</param> /// <param name="P">Population</param> public abstract void RunGA( State Situation, Population P );
/// <summary> /// 足りないときのCovering /// </summary> /// <param name="S">situation</param> /// <param name="P">Population</param> protected abstract void Covering( State S, Population P );
// Sigmaは飾り
public override void Update( Population Pop, double P, StdList Sigma )
{
double SumNumerosity = 0;
foreach( Classifier C in this.CList )
{
SumNumerosity += C.N;
}
foreach( Classifier C in this.CList )
{
C.Exp++;
if( C.Exp < 1 / Configuration.Beta )
{
C.P += ( P - C.P ) / C.Exp;
}
else
{
C.P += Configuration.Beta * ( P - C.P );
}
if( C.Exp < Configuration.Beta )
{
C.Epsilon += ( Math.Abs( P - C.P ) - C.Epsilon ) / C.Exp;
}
else
{
C.Epsilon += Configuration.Beta * ( Math.Abs( P - C.P ) - C.Epsilon );
}
if( C.Exp < Configuration.Beta )
{
C.As += ( SumNumerosity - C.As ) / C.Exp;
}
else
{
C.As += Configuration.Beta * ( SumNumerosity - C.As );
}
//if( C.C.state == "11####" && C.A == '0' )
//{
// Configuration.ESW.WriteLine( Configuration.T + "," + C.F + "," + C.Kappa + "," + C.Epsilon_0 + "," + C.Epsilon + "," + C.Exp + "," + Math.Sqrt( C.S / ( C.St - 1 ) ) );
// //Console.WriteLine( Configuration.T + " " + this.Exp );
//}
// 標準偏差計算
C.St++;
double X = P - C.M;
C.M += X / C.St;
C.S += ( C.St - 1 ) * X * X / C.St;
}
this.UpdateFitness();
if( Configuration.DoActionSetSubsumption )
{
this.Subsumption( Pop );
}
}