nojhan/paradiseo
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

Migration from SVN

Browse source
This commit is contained in:
quemy 2012-08-30 11:30:11 +02:00
commit 8cd56f37db
29069 changed files with 0 additions and 4096888 deletions
Download patch file Download diff file Expand all files Collapse all files

78
branches/rc2.0/eo/src/ga/eoPBILOrg.h
View file

@ -1,78 +0,0 @@
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// eoPBILOrg.h
// (c) Marc Schoenauer, Maarten Keijzer, 2001
/*
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
Contact: Marc.Schoenauer@polytechnique.fr
mkeijzer@dhi.dk
*/
//-----------------------------------------------------------------------------
#ifndef _eoPBILOrg_H
#define _eoPBILOrg_H
#include <eoDistribUpdater.h>
#include <ga/eoPBILDistrib.h>
/**
* Distribution Class for PBIL algorithm
* (Population-Based Incremental Learning, Baluja and Caruana 95)
*
* This class implements the update rule from the original paper:
*
* p(i)(t+1) = (1-LR)*p(i)(t) + LR*best(i)
*/
template <class EOT>
class eoPBILOrg : public eoDistribUpdater<EOT>
{
public:
/** Ctor with size of genomes, and update parameters */
eoPBILOrg(double _LR, double _tolerance=0.0 ) :
LR(_LR), maxBound(1.0-_tolerance), minBound(_tolerance)
{}
/** Update the distribution from the current population */
virtual void operator()(eoDistribution<EOT> & _distrib, eoPop<EOT>& _pop)
{
const EOT & best = _pop.best_element();
eoPBILDistrib<EOT>& distrib = dynamic_cast<eoPBILDistrib<EOT>&>(_distrib);
std::vector<double> & p = distrib.value();
for (unsigned g=0; g<distrib.size(); g++)
{
// double & r = value()[g];
p[g] *= (1-LR);
if ( best[g] )
p[g] += LR;
// else nothing
// stay away from 0 and 1
p[g] = std::min(maxBound, p[g]);
p[g] = std::max(minBound, p[g]);
}
}
private:
double LR; // learning rate for best guys
double maxBound, minBound; // proba stay away from 0 and 1 by at least tolerance
};
#endif