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#include "genetic/explicitsimulation.h"
#include "genetic/operator.h"
#include "genetic/fitnessfunction.h"
#include <bu/random.h>
#include <bu/sio.h>
using namespace Bu;
Genetic::ExplicitSimulation::ExplicitSimulation( Genetic::Operator *pOper,
Genetic::FitnessFunction *pFunc, int iPopSize, float fKeep,
float fRandom, bool bKeepBest ) :
pOper( pOper ),
pFunc( pFunc ),
iPopSize( iPopSize ),
fKeep( fKeep ),
fRandom( fRandom ),
bKeepBest( bKeepBest )
{
for( int j = 0; j < iPopSize; j++ )
{
xPop.addPhenotype( pOper->random() );
}
updateFitness();
}
Genetic::ExplicitSimulation::~ExplicitSimulation()
{
delete pOper;
delete pFunc;
}
void Genetic::ExplicitSimulation::timestep()
{
PhenotypeList lNew;
int iChildren = iPopSize*(1.0-fKeep-fRandom);
// Create children
for( int j = 0; j < iChildren; j++ )
{
PhenotypeList lParents;
for( int k = 0; k < pOper->parentCount(); k++ )
lParents.append( xPop.getPhenotype( selectWeighted() ) );
lNew.append( pOper->mate( lParents ) );
}
// Select phenotypes for keeping
int iKeep = iPopSize*fKeep;
FitnessHash hTempFitness;
for( int j = 0; j < iKeep; j++ )
{
Genetic::PhenotypeId id = selectWeighted();
lNew.append( xPop.takePhenotype( id ) );
hTempFitness.insert( id, hFitness.get( id ) );
hFitness.erase( id );
dTotalFitness -= hTempFitness.get( id );
}
if( bKeepBest && hFitness.has( uMaxFitness ) )
{
lNew.append( xPop.takePhenotype( uMaxFitness ) );
hTempFitness.insert( uMaxFitness, hFitness.get( uMaxFitness ) );
hFitness.erase( uMaxFitness );
dTotalFitness -= hTempFitness.get( uMaxFitness );
}
// Fill in the remainder with random phenotypes
while( lNew.getSize() < iPopSize )
{
lNew.append( pOper->random() );
}
// Refill the population
hFitness = hTempFitness;
xPop.clear();
xPop.timestep();
for( PhenotypeList::iterator i = lNew.begin(); i; i++ )
{
xPop.addPhenotype( *i );
}
updateFitness();
}
Genetic::PhenotypeId Genetic::ExplicitSimulation::selectWeighted()
{
double dSel = Bu::Random::randNorm()*dTotalFitness;
double dRun = 0.0;
for( FitnessHash::iterator i = hFitness.begin(); i; i++ )
{
dRun += *i;
if( dSel < dRun )
return i.getKey();
}
sio << "Genetic::ExplicitSimulation::selectWeighted() - failed, picked max"
<< sio.nl;
return uMaxFitness;
}
void Genetic::ExplicitSimulation::updateFitness()
{
dMinFitness = -1.0;
dTotalFitness = 0.0;
for( Population::iterator i = xPop.begin(); i; i++ )
{
double dFitness;
if( hFitness.has( i.getKey() ) )
{
dFitness = hFitness.get( i.getKey() );
}
else
{
dFitness = (*pFunc)( *i );
if( dFitness < 0.0 )
dFitness = 0.0;
hFitness.insert( i.getKey(), dFitness );
}
dTotalFitness += dFitness;
if( dMinFitness < 0.0 )
{
dMinFitness = dMaxFitness = dFitness;
uMaxFitness = i.getKey();
}
else if( dMinFitness > dFitness )
{
dMinFitness = dFitness;
}
else if( dMaxFitness < dFitness )
{
dMaxFitness = dFitness;
uMaxFitness = i.getKey();
}
}
}
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