神经网络入门 ，源码3

神经网络入门 源码3

说明：以下为与《神经网络入门》连载9-11相关的程序“有监督的学习”全部C++语言源码，不含头文件。这是《游戏编程中的人工智能技术》一书所附CD中的内容，仅供已阅读《神经网络入门》连载9-11的读者进一步深入阅读参考，我在源码中未添加任何中文解释，而且今后也不会为其中内容进行解释、答疑，甚至不关心是否有读者“到此一游”过。但可以肯定代码不会有差错，我已实际使用这些源文件编译过（用Borland C++，V3），完全能通过，并生成能正确运行的执行程序。

目  录

1. C2DMatrix.cpp

#include "C2DMatrix.h"


/////////////////////////////////////////////////////////////////////
//
// Matrix methods
//
/////////////////////////////////////////////////////////////////////
//create an identity matrix
void C2DMatrix::Identity()
{
m_Matrix._11 = 1.0f; m_Matrix._12 = 0.0f; m_Matrix._13 = 0.0f;


m_Matrix._21 = 0.0f; m_Matrix._22 = 1.0f; m_Matrix._23 = 0.0f;


m_Matrix._31 = 0.0f; m_Matrix._32 = 0.0f; m_Matrix._33 = 1.0f;


}


//create a transformation matrix
void C2DMatrix::Translate(double x, double y)
{
S2DMatrix mat;

mat._11 = 1.0f; mat._12 = 0.0f; mat._13 = 0.0f;

mat._21 = 0.0f; mat._22 = 1.0f; mat._23 = 0.0f;

mat._31 = x;    mat._32 = y;    mat._33 = 1.0f;

//and multiply
  S2DMatrixMultiply(mat);
}


//create a scale matrix
void C2DMatrix::Scale(double xScale, double yScale)
{
S2DMatrix mat;

mat._11 = xScale; mat._12 = 0.0f; mat._13 = 0.0f;

mat._21 = 0.0f; mat._22 = yScale; mat._23 = 0.0f;

mat._31 = 0.0f; mat._32 = 0.0f; mat._33 = 1.0f;

//and multiply
  S2DMatrixMultiply(mat);
}

//create a rotation matrix
void C2DMatrix::Rotate(double rot)
{
S2DMatrix mat;


double Sin = sin(rot);
double Cos = cos(rot);

mat._11 = Cos;  mat._12 = Sin; mat._13 = 0.0f;

mat._21 = -Sin; mat._22 = Cos; mat._23 = 0.0f;

mat._31 = 0.0f; mat._32 = 0.0f;mat._33 = 1.0f;

//and multiply
  S2DMatrixMultiply(mat);
}


//multiply two matrices together
void C2DMatrix::S2DMatrixMultiply(S2DMatrix &mIn)
{
S2DMatrix mat_temp;

//first row
mat_temp._11 = (m_Matrix._11*mIn._11) + (m_Matrix._12*mIn._21) + (m_Matrix._13*mIn._31);
mat_temp._12 = (m_Matrix._11*mIn._12) + (m_Matrix._12*mIn._22) + (m_Matrix._13*mIn._32);
mat_temp._13 = (m_Matrix._11*mIn._13) + (m_Matrix._12*mIn._23) + (m_Matrix._13*mIn._33);


//second
mat_temp._21 = (m_Matrix._21*mIn._11) + (m_Matrix._22*mIn._21) + (m_Matrix._23*mIn._31);
mat_temp._22 = (m_Matrix._21*mIn._12) + (m_Matrix._22*mIn._22) + (m_Matrix._23*mIn._32);
mat_temp._23 = (m_Matrix._21*mIn._13) + (m_Matrix._22*mIn._23) + (m_Matrix._23*mIn._33);


//third
mat_temp._31 = (m_Matrix._31*mIn._11) + (m_Matrix._32*mIn._21) + (m_Matrix._33*mIn._31);
mat_temp._32 = (m_Matrix._31*mIn._12) + (m_Matrix._32*mIn._22) + (m_Matrix._33*mIn._32);
mat_temp._33 = (m_Matrix._31*mIn._13) + (m_Matrix._32*mIn._23) + (m_Matrix._33*mIn._33);


m_Matrix = mat_temp;
}


//applies a 2D transformation matrix to a std::vector of SPoints
void C2DMatrix::TransformSPoints(vector<SPoint> &vPoint)
{
for (int i=0; i<vPoint.size(); ++i)
{
double tempX =(m_Matrix._11*vPoint[i].x) + (m_Matrix._21*vPoint[i].y) + (m_Matrix._31);


double tempY = (m_Matrix._12*vPoint[i].x) + (m_Matrix._22*vPoint[i].y) + (m_Matrix._32);

vPoint[i].x = tempX;


vPoint[i].y = tempY;


}
}

2. CController.cpp

#include "CController.h"

//these hold the geometry of the sweepers and the mines
const int NumSweeperVerts = 16;
const SPoint sweeper[NumSweeperVerts] = {SPoint(-1, -1),
                                         SPoint(-1, 1),
                                         SPoint(-0.5, 1),
                                         SPoint(-0.5, -1),


                                         SPoint(0.5, -1),
                                         SPoint(1, -1),
                                         SPoint(1, 1),
                                         SPoint(0.5, 1),
                                         
                                         SPoint(-0.5, -0.5),
                                         SPoint(0.5, -0.5),


                                         SPoint(-0.5, 0.5),
                                         SPoint(-0.25, 0.5),
                                         SPoint(-0.25, 1.75),
                                         SPoint(0.25, 1.75),
                                         SPoint(0.25, 0.5),
                                         SPoint(0.5, 0.5)};




const int NumObjectVerts = 42;
const SPoint objects[NumObjectVerts] = {SPoint(80, 60),
                                        SPoint(200,60),
                                        SPoint(200,60),
                                        SPoint(200,100),
                                        SPoint(200,100),
                                        SPoint(160,100),
                                        SPoint(160,100),
                                        SPoint(160,200),
                                        SPoint(160,200),
                                        SPoint(80,200),
                                        SPoint(80,200),
                                        SPoint(80,60),


                                        SPoint(250,100),
                                        SPoint(300,40),
                                        SPoint(300,40),
                                        SPoint(350,100),
                                        SPoint(350,100),
                                        SPoint(250, 100),


                                        SPoint(220,180),
                                        SPoint(320,180),
                                        SPoint(320,180),
                                        SPoint(320,300),
                                        SPoint(320,300),
                                        SPoint(220,300),
                                        SPoint(220,300),
                                        SPoint(220,180),


                                        SPoint(12,15),
                                        SPoint(380, 15),
                                        SPoint(380,15),
                                        SPoint(380,360),
                                        SPoint(380,360),                                
                                        SPoint(12,360),
                                        SPoint(12,360),
                                        SPoint(12,340),
                                        SPoint(12,340),
                                        SPoint(100,290),
                                        SPoint(100,290),
                                        SPoint(12,240),
                                        SPoint(12,240),
                                        SPoint(12,15)，



//---------------------------------------constructor---------------------
//
// initilaize the sweepers, their brains and the GA factory
//
//-----------------------------------------------------------------------
CController::CController(HWND hwndMain): m_NumSweepers(CParams::iNumSweepers), 
                    m_pGA(NULL),
                    m_bFastRender(false),
                    m_iTicks(0),
                    m_hwndMain(hwndMain),
                    m_iGenerations(0),
                                         cxClient(CParams::WindowWidth),
                                         cyClient(CParams::WindowHeight)
                                        
{
//let's create the mine sweepers
for (int i=0; i<m_NumSweepers; ++i)
{
m_vecSweepers.push_back(CMinesweeper());
}


//get the total number of weights used in the sweepers
//NN so we can initialise the GA
m_NumWeightsInNN = m_vecSweepers[0].GetNumberOfWeights();


  //calculate the neuron placement in the weight vector
  vector<int> SplitPoints = m_vecSweepers[0].CalculateSplitPoints();


//initialize the Genetic Algorithm class
m_pGA = new CGenAlg(m_NumSweepers,
                      CParams::dMutationRate,
                   CParams::dCrossoverRate,
                   m_NumWeightsInNN,
                      SplitPoints);


//Get the weights from the GA and insert into the sweepers brains
m_vecThePopulation = m_pGA->GetChromos();


for (i=0; i<m_NumSweepers; i++)
  {
m_vecSweepers[i].PutWeights(m_vecThePopulation[i].vecWeights);
  }




//create the pens for the graph drawing
m_BluePen        = CreatePen(PS_SOLID, 1, RGB(0, 0, 255));
m_RedPen         = CreatePen(PS_SOLID, 1, RGB(255, 0, 0));
m_GreenPen       = CreatePen(PS_SOLID, 1, RGB(0, 255, 0));
  m_GreyPenDotted  = CreatePen(PS_DOT, 1, RGB(200, 200, 200));
  m_RedPenDotted   = CreatePen(PS_DOT, 1, RGB(250, 200, 200));


m_OldPen = NULL;


  //and the brushes
  m_BlueBrush = CreateSolidBrush(RGB(0,0,244));
  m_RedBrush = CreateSolidBrush(RGB(150,0,0));


//fill the vertex buffers
for (i=0; i<NumSweeperVerts; ++i)
{
m_SweeperVB.push_back(sweeper[i]);
}


  for (i=0; i<NumObjectVerts; ++i)
  {
    m_ObjectsVB.push_back(objects[i]);
  }
}


//--------------------------------------destructor-------------------------------------
//
//--------------------------------------------------------------------------------------
CController::~CController()
{
if(m_pGA)
  {
    delete m_pGA;
  }


DeleteObject(m_BluePen);
DeleteObject(m_RedPen);
DeleteObject(m_GreenPen);
DeleteObject(m_OldPen);
  DeleteObject(m_GreyPenDotted);
  DeleteObject(m_RedPenDotted);
  DeleteObject(m_BlueBrush);
  DeleteObject(m_RedBrush);
}




//---------------------WorldTransform--------------------------------
//
// sets up the translation matrices for the mines and applies the
// world transform to each vertex in the vertex buffer passed to this
// method.
//-------------------------------------------------------------------
void CController::WorldTransform(vector<SPoint> &VBuffer,
                                 SVector2D      vPos,
                                 double         rotation,
                                 double         scale)
{
//create the world transformation matrix
C2DMatrix matTransform;

//scale
matTransform.Scale(scale, scale);


    //rotate
matTransform.Rotate(rotation);

//translate
matTransform.Translate(vPos.x, vPos.y);

//transform the ships vertices
matTransform.TransformSPoints(VBuffer);
}

//-------------------------------------Update---------------------------------------
//
// This is the main workhorse. The entire simulation is controlled from here.
//
// The comments should explain what is going on adequately.
//--------------------------------------------------------------------------------------
bool CController::Update()
{

//run the sweepers through CParams::iNumTicks amount of cycles. During this loop each
//sweepers NN is constantly updated with the appropriate information from its 
//surroundings. The output from the NN is obtained and the sweeper is moved. If
//it encounters a mine its fitness is updated appropriately,
if (m_iTicks++ < CParams::iNumTicks)
{
for (int i=0; i<m_NumSweepers; ++i)
{
//update the NN and position
if (!m_vecSweepers[i].Update(m_ObjectsVB))
{
//error in processing the neural net
MessageBox(m_hwndMain, "Wrong amount of NN inputs!", "Error", MB_OK);


return false;
}
}
}


//**We have completed another generation.


//Time to run the GA and update the sweepers with their new NNs
else
{
    int BestCellCoverage = 0;


    for (int swp=0; swp<m_vecSweepers.size(); ++swp)
    {
       //add up all the penalties and calculate a fitness score
       m_vecSweepers[swp].EndOfRunCalculations();


       //update the fitness score stored in the GA with this score
m_vecThePopulation[swp].dFitness = m_vecSweepers[swp].Fitness();


       if (m_vecSweepers[swp].NumCellsVisited() > BestCellCoverage)
       {
         BestCellCoverage = m_vecSweepers[swp].NumCellsVisited();
       }
    }


//update the stats to be used in our stat window
m_vecAvFitness.push_back(fabs(m_pGA->AverageRawFitness()));
m_vecBestFitness.push_back(fabs(m_pGA->BestRawFitness()));


//increment the generation counter
++m_iGenerations;


//reset cycles
m_iTicks = 0;


//insert the sweepers chromosones into the GA factory and
//run the factory to create a new population
m_vecThePopulation = m_pGA->Epoch(m_vecThePopulation);

//insert the new (hopefully)improved brains back into the sweepers
    //and reset their positions etc
    for (int i=0; i<m_NumSweepers; ++i)
{
m_vecSweepers[i].PutWeights(m_vecThePopulation[i].vecWeights);

m_vecSweepers[i].Reset();
}
}


return true;
}
//------------------------------------Render()--------------------------------------
//
//----------------------------------------------------------------------------------
void CController::Render(HDC surface)
{
//render the stats
string s = "Generation: " + itos(m_iGenerations);
TextOut(surface, 5, 0, s.c_str(), s.size());


//do not render if running at accelerated speed
if (!m_bFastRender)
{
//display the penalties
    m_vecSweepers[0].Render(surface);
    
    //render the objects
    for (int i=0; i<NumObjectVerts; i+=2)
    {
      MoveToEx(surface, m_ObjectsVB[i].x, m_ObjectsVB[i].y, NULL);


      LineTo(surface, m_ObjectsVB[i+1].x, m_ObjectsVB[i+1].y);
    }

    //we want the fittest displayed in green
    m_OldPen = (HPEN)SelectObject(surface, m_GreenPen);


//render the sweepers
for (i=0; i<m_vecSweepers.size(); i++)
{
if (i < CParams::iNumElite)
      {
        SelectObject(surface,m_OldPen);        
      }


      else
      {
        SelectObject(surface, m_GreyPenDotted);
      }


      //render red if collided and elite
      if ( m_vecSweepers[i].Collided() && (i < CParams::iNumElite) )
      {
        SelectObject(surface, m_RedPen);
      }
      
      //render dotted red if collided and not elite
      if ( m_vecSweepers[i].Collided() && (i > CParams::iNumElite) )
      {
        SelectObject(surface, m_RedPenDotted);
      }
      
      //grab the sweeper vertices
vector<SPoint> sweeperVB = m_SweeperVB;


//transform the vertex buffer
m_vecSweepers[i].WorldTransform(sweeperVB, m_vecSweepers[i].Scale());


//draw the sweeper left track
MoveToEx(surface, (int)sweeperVB[0].x, (int)sweeperVB[0].y, NULL);


for (int vert=1; vert<4; ++vert)
{
LineTo(surface, (int)sweeperVB[vert].x, (int)sweeperVB[vert].y);
}


      LineTo(surface, (int)sweeperVB[0].x, (int)sweeperVB[0].y);


      //draw the sweeper right track
MoveToEx(surface, (int)sweeperVB[4].x, (int)sweeperVB[4].y, NULL);


for (vert=5; vert<8; ++vert)
{
LineTo(surface, (int)sweeperVB[vert].x, (int)sweeperVB[vert].y);
}


      LineTo(surface, (int)sweeperVB[4].x, (int)sweeperVB[4].y);


      MoveToEx(surface, (int)sweeperVB[8].x, (int)sweeperVB[8].y, NULL);
      LineTo(surface, (int)sweeperVB[9].x, (int)sweeperVB[9].y);


      MoveToEx(surface, (int)sweeperVB[10].x, (int)sweeperVB[10].y, NULL);


      for (vert=11; vert<16; ++vert)
{
LineTo(surface, (int)sweeperVB[vert].x, (int)sweeperVB[vert].y);
}


}


    //render the sensors
    for (i=0; i<CParams::iNumElite; ++i)
    {
      //grab each sweepers sensor data
      vector<SPoint> tranSensors    = m_vecSweepers[i].Sensors();
      vector<double>   SensorReadings = m_vecSweepers[i].SensorReadings();
      vector<double> MemoryReadings = m_vecSweepers[i].MemoryReadings();


      for (int sr=0; sr<tranSensors.size(); ++sr)
      {
        if (SensorReadings[sr] > 0)
        {
          SelectObject(surface, m_RedPen);
        }


        else
        {
          SelectObject(surface, m_GreyPenDotted);
        }
        
        //make sure we clip the drawing of the sensors or we will get
        //unwanted artifacts appearing
        if (!((fabs(m_vecSweepers[i].Position().x - tranSensors[sr].x) >
              (CParams::dSensorRange+1))||
              (fabs(m_vecSweepers[i].Position().y - tranSensors[sr].y) >
              (CParams::dSensorRange+1))))
        {
        
          MoveToEx(surface,
                   (int)m_vecSweepers[i].Position().x,
                   (int)m_vecSweepers[i].Position().y,
                   NULL);


          LineTo(surface, (int)tranSensors[sr].x, (int)tranSensors[sr].y);


          //render the cell sensors
          RECT rect;
          rect.left  = (int)tranSensors[sr].x - 2;
          rect.right = (int)tranSensors[sr].x + 2;
          rect.top   = (int)tranSensors[sr].y - 2;
          rect.bottom= (int)tranSensors[sr].y + 2;
          
          if (MemoryReadings[sr] < 0)
          {


            FillRect(surface, &rect, m_BlueBrush);
          }


          else
          {
            FillRect(surface, &rect, m_RedBrush);
          }
          
        }
      }
    }


    SelectObject(surface, m_OldPen);


}//end if


  else
  {
    PlotStats(surface);
  }


}
//--------------------------PlotStats-------------------------------------
//
//  Given a surface to draw on this function displays stats and a crude
//  graph showing best and average fitness
//------------------------------------------------------------------------
void CController::PlotStats(HDC surface)
{
   
    string s = "Best Fitness:       " + ftos(m_pGA->BestRawFitness());
 TextOut(surface, 5, 20, s.c_str(), s.size());


     s = "Average Fitness: " + ftos(m_pGA->AverageRawFitness());
 TextOut(surface, 5, 40, s.c_str(), s.size());
    
    //render the graph
    float HSlice = (float)cxClient/(m_iGenerations+1);
    float VSlice = (float)cyClient/((m_pGA->BestRawFitness()+1) * 1.5);


    //plot the graph for the best fitness
    float x = 0;
    
    m_OldPen = (HPEN)SelectObject(surface, m_RedPen);


    MoveToEx(surface, 0, cyClient, NULL);
    
    for (int i=0; i<m_vecBestFitness.size(); ++i)
    {
       LineTo(surface, x, (cyClient - VSlice*m_vecBestFitness[i]));


       x += HSlice;
    }


    //plot the graph for the average fitness
    x = 0;


    SelectObject(surface, m_BluePen);


    MoveToEx(surface, 0, cyClient, NULL);
    
    for (i=0; i<m_vecAvFitness.size(); ++i)
    {
       LineTo(surface, x, (cyClient - VSlice*m_vecAvFitness[i]));


       x += HSlice;
    }


    //replace the old pen
    SelectObject(surface, m_OldPen);
}

3. CGenAlg.cpp

#include "CGenAlg.h"

//-----------------------------------constructor-------------------------
//
// sets up the population with random floats
//
//-----------------------------------------------------------------------
CGenAlg::CGenAlg(int  popsize,
                 double MutRat,
                 double CrossRat,
                 int  numweights,
                 vector<int> splits) :m_iPopSize(popsize),
                                      m_dMutationRate(MutRat),
                 m_dCrossoverRate(CrossRat),
                 m_iChromoLength(numweights),
                 m_dTotalFitness(0),
                 m_cGeneration(0),
                 m_iFittestGenome(0),
                 m_dBestFitness(0),
                 m_dWorstFitness(99999999),
                 m_dAverageFitness(0),
                                      m_vecSplitPoints(splits)
{
//initialise population with chromosomes consisting of random
//weights and all fitnesses set to zero
for (int i=0; i<m_iPopSize; ++i)
{
m_vecPop.push_back(SGenome());


for (int j=0; j<m_iChromoLength; ++j)
{
m_vecPop[i].vecWeights.push_back(RandomClamped());
}
}
}


//---------------------------------Mutate--------------------------------
//
// mutates a chromosome by perturbing its weights by an amount not 
// greater than MAX_PERTURBATION
//-----------------------------------------------------------------------
void CGenAlg::Mutate(vector<double> &chromo)
{
//traverse the chromosome and mutate each weight dependent
//on the mutation rate
for (int i=0; i<chromo.size(); ++i)
{
//do we perturb this weight?
if (RandFloat() < m_dMutationRate)
{
//add a small value to the weight
chromo[i] += (RandomClamped() * CParams::dMaxPerturbation);
}
}
}

//---------------------------- CrossoverAtSplits -------------------------
//
// performs crossover at the neuron bounderies. See the end of chapter 7
// for details
//-------------------------------------------------------------------------
void CGenAlg::CrossoverAtSplits(const vector<double> &mum,
                                const vector<double> &dad,
                                vector<double>       &baby1,
                                vector<double>       &baby2)
{
  //just return parents as offspring dependent on the rate
//or if parents are the same
if ( (RandFloat() > m_dCrossoverRate) || (mum == dad)) 
{
baby1 = mum;
baby2 = dad;


return;
}


//determine two crossover points
  int Index1 = RandInt(0, m_vecSplitPoints.size()-2);
  int Index2 = RandInt(Index1, m_vecSplitPoints.size()-1);


int cp1 = m_vecSplitPoints[Index1];
  int cp2 = m_vecSplitPoints[Index2];


//create the offspring
for (int i=0; i<mum.size(); ++i)
{
    if ( (i<cp1) || (i>=cp2) )
    {
 //keep the same genes if outside of crossover points
      baby1.push_back(mum[i]);
 baby2.push_back(dad[i]);
    }


    else
    {
      //switch over the belly block
      baby1.push_back(dad[i]);
 baby2.push_back(mum[i]);
    }
      
}

return;
}


//---------------------------- TournamentSelection -----------------
//
//  performs standard tournament selection given a number of genomes to
//  sample from each try.
//------------------------------------------------------------------------
SGenome CGenAlg::TournamentSelection(int N)
{
  double BestFitnessSoFar = -999999;
  
  int ChosenOne = 0;


  //Select N members from the population at random testing against 
  //the best found so far
  for (int i=0; i<N; ++i)
  {
    int ThisTry = RandInt(0, m_iPopSize-1);


    if (m_vecPop[ThisTry].dFitness > BestFitnessSoFar)
    {
      ChosenOne = ThisTry;


      BestFitnessSoFar = m_vecPop[ThisTry].dFitness;
    }
  }


  //return the champion
  return m_vecPop[ChosenOne];
}
//-----------------------------------Epoch()-----------------------------
//
// takes a population of chromosones and runs the algorithm through one
// cycle.
// Returns a new population of chromosones.
//-----------------------------------------------------------------------
vector<SGenome> CGenAlg::Epoch(vector<SGenome> &old_pop)
{
//assign the given population to the classes population
  m_vecPop = old_pop;


  //reset the appropriate variables
  Reset();


  //create a temporary vector to store new chromosones
vector <SGenome> vecNewPop;


  CalculateBestWorstAvTot();
  
  //sort the population (for scaling and elitism)
  sort(m_vecPop.begin(), m_vecPop.end());


//Now to add a little elitism we shall add in some copies of the
//fittest genomes. Make sure we add an EVEN number or the roulette
  //wheel sampling will crash
if (!(CParams::iNumCopiesElite * CParams::iNumElite % 2))
{
GrabNBest(CParams::iNumElite, CParams::iNumCopiesElite, vecNewPop);
}

 //--------------now to enter the GA loop

//repeat until a new population is generated
while (vecNewPop.size() < m_iPopSize)
{
    //select using tournament selection for a change
    SGenome mum = TournamentSelection(CParams::iTournamentCompetitors);
SGenome dad = TournamentSelection(CParams::iTournamentCompetitors);

//create some offspring via crossover
vector<double>baby1, baby2;

CrossoverAtSplits(mum.vecWeights, dad.vecWeights, baby1, baby2);

//now we mutate
Mutate(baby1);
Mutate(baby2);

//now copy into vecNewPop population
vecNewPop.push_back( SGenome(baby1, 0) );
vecNewPop.push_back( SGenome(baby2, 0) );
}

//finished so assign new pop back into m_vecPop
m_vecPop = vecNewPop;

return m_vecPop;
}


//-------------------------GrabNBest----------------------------------
//
// This works like an advanced form of elitism by inserting NumCopies
//  copies of the NBest most fittest genomes into a population vector
//--------------------------------------------------------------------
void CGenAlg::GrabNBest(int            NBest,
                        const int      NumCopies,
                        vector<SGenome> &Pop)
{
  //add the required amount of copies of the n most fittest 
//to the supplied vector
while(NBest--)
{
for (int i=0; i<NumCopies; ++i)
{
Pop.push_back(m_vecPop[(m_iPopSize - 1) - NBest]);
 }
}
}


//-----------------------CalculateBestWorstAvTot-----------------------
//
// calculates the fittest and weakest genome and the average/total 
// fitness scores
//---------------------------------------------------------------------
void CGenAlg::CalculateBestWorstAvTot()
{
m_dTotalFitness = 0;

double HighestSoFar = 0;
double LowestSoFar  = 9999999;

for (int i=0; i<m_iPopSize; ++i)
{
//update fittest if necessary
if (m_vecPop[i].dFitness > HighestSoFar)
{
HighestSoFar = m_vecPop[i].dFitness;

m_iFittestGenome = i;


m_dBestFitness= HighestSoFar;
}

//update worst if necessary
if (m_vecPop[i].dFitness < LowestSoFar)
{
LowestSoFar = m_vecPop[i].dFitness;

m_dWorstFitness = LowestSoFar;
}

m_dTotalFitness+= m_vecPop[i].dFitness;


}//next chromo

m_dAverageFitness = m_dTotalFitness / m_iPopSize;
}

//-------------------------Reset()------------------------------
//
// resets all the relevant variables ready for a new generation
//--------------------------------------------------------------
void CGenAlg::Reset()
{
m_dTotalFitness= 0;
m_dBestFitness= 0;
m_dWorstFitness= 9999999;
m_dAverageFitness= 0;
}