Пример #1
0
        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.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.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 (Child_1.C.state[4] == '0' & Child_1.C.state[7] == '1')//"bath0 rehabi1"
                {
                    Configuration.Problem.WriteLine(Child_1.C.state + "," + Configuration.T + "," + Child_1.P + "," + Child_1.M + "," + Child_1.Epsilon + "," + Child_1.F + ","
                                                    + Child_1.N + "," + Child_1.Exp + "," + Child_1.Ts + "," + Child_1.As + "," + Child_1.Kappa + "," + Child_1.Epsilon_0 + "," + Child_1.St + "," + Child_1.GenerateTime + ", child 2 ");
                    Configuration.Problem.WriteLine(Parent_1.C.state + "," + Configuration.T + "," + Parent_1.P + "," + Parent_1.M + "," + Parent_1.Epsilon + "," + Parent_1.F + ","
                                                    + Parent_1.N + "," + Parent_1.Exp + "," + Parent_1.Ts + "," + Parent_1.As + "," + Parent_1.Kappa + "," + Parent_1.Epsilon_0 + "," + Parent_1.St + "," + Parent_1.GenerateTime + ",Parent1");

                    Configuration.Problem.WriteLine(Parent_2.C.state + "," + Configuration.T + "," + Parent_2.P + "," + Parent_2.M + "," + Parent_2.Epsilon + "," + Parent_2.F + ","
                                                    + Parent_2.N + "," + Parent_2.Exp + "," + Parent_2.Ts + "," + Parent_2.As + "," + Parent_2.Kappa + "," + Parent_2.Epsilon_0 + "," + Parent_2.St + "," + Parent_2.GenerateTime + ",Parent2");
                }

                if (Child_2.C.state[4] == '0' & Child_2.C.state[7] == '1')//"bath0 rehabi1"
                {
                    Configuration.Problem.WriteLine(Child_2.C.state + "," + Configuration.T + "," + Child_2.P + "," + Child_2.M + "," + Child_2.Epsilon + "," + Child_2.F + ","
                                                    + Child_2.N + "," + Child_2.Exp + "," + Child_2.Ts + "," + Child_2.As + "," + Child_2.Kappa + "," + Child_2.Epsilon_0 + "," + Child_2.St + "," + Child_2.GenerateTime + ",child 2");
                    Configuration.Problem.WriteLine(Parent_1.C.state + "," + Configuration.T + "," + Parent_1.P + "," + Parent_1.M + "," + Parent_1.Epsilon + "," + Parent_1.F + ","
                                                    + Parent_1.N + "," + Parent_1.Exp + "," + Parent_1.Ts + "," + Parent_1.As + "," + Parent_1.Kappa + "," + Parent_1.Epsilon_0 + "," + Parent_1.St + "," + Parent_1.GenerateTime + ",Parent1");

                    Configuration.Problem.WriteLine(Parent_2.C.state + "," + Configuration.T + "," + Parent_2.P + "," + Parent_2.M + "," + Parent_2.Epsilon + "," + Parent_2.F + ","
                                                    + Parent_2.N + "," + Parent_2.Exp + "," + Parent_2.Ts + "," + Parent_2.As + "," + Parent_2.Kappa + "," + Parent_2.Epsilon_0 + "," + Parent_2.St + "," + Parent_2.GenerateTime + ",Parent2");
                }
                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();
                }
            }
        }
Пример #2
0
        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();
                }
            }
        }