main.cpp

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/*
    This program is free software; you can redistribute it and/or modify
    it under the terms of the GNU 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 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: [e-mail], http://geneura.ugr.es
             [e-mail]
*/

#ifdef _MSC_VER
#pragma warning(disable:4786)
#endif

#ifdef HAVE_CONFIG_H
#include <config.h>
#endif

#include <iostream>
#include "gp/eoParseTree.h"
#include "eo"

using namespace gp_parse_tree;
using namespace std;

//-----------------------------------------------------------------------------

#include "node.h"
#include "parameters.h"
#include "fitness.h"


// TYPE DECLARATIONS FOR GP


typedef eoParseTree<FitnessType, Node > EoType;
typedef eoPop<EoType> Pop;

//-----------------------------------------------------------------------------

int main(int argc, char *argv[])
{

	// the vector containing the possible nodes
	vector<Node> initSequence;

	// initialise parameters
	Parameters parameter(argc, argv);

	// set the randomseed
	rng.reseed(parameter.randomseed);

	 // Create a generation counter
    	eoValueParam<unsigned> generationCounter(0, "Gen.");

    	// Create an incrementor (sub-class of eoUpdater). Note that the
    	// parameter's value is passed by reference,
    	// so every time the incrementer is updated (every generation),
    	// the data in generationCounter will change.
    	eoIncrementor<unsigned> increment(generationCounter.value());


	// create an instantiation of the fitness/evaluation function
	// it initializes the initSequence vector
	// the parameters are passed on as well
        RegFitness eval(generationCounter, initSequence, parameter);

	// Depth Initializor, set for Ramped Half and Half Initialization
        eoParseTreeDepthInit<FitnessType, Node> initializer(parameter.InitMaxDepth, initSequence, true, true);

	// create the initial population
        Pop pop(parameter.population_size, initializer);

	// and evaluate the individuals
        apply<EoType>(eval, pop);

	generationCounter.value()++; // set the generationCounter to 1


    	// define X-OVER

	eoSubtreeXOver<FitnessType, Node>   xover(parameter.MaxSize);

	// define MUTATION
      eoBranchMutation<FitnessType, Node> mutation(initializer, parameter.MaxSize);
//      eoExpansionMutation<FitnessType, Node> mutation(initializer, parameter.MaxSize);
//	eoCollapseSubtreeMutation<FitnessType, Node> mutation(initializer, parameter.MaxSize);
//	eoPointMutation<FitnessType, Node> mutation(initSequence);
//	eoHoistMutation<FitnessType, Node> mutation;

	// The operators are  encapsulated into an eoTRansform object,
    	// that performs sequentially crossover and mutation
	eoSGATransform<EoType> transform(xover, parameter.xover_rate, mutation, parameter.mutation_rate);

	// The robust tournament selection
	// in our case 5-tournament selection
    	eoDetTournamentSelect<EoType> selectOne(parameter.tournamentsize);
	// is now encapsulated in a eoSelectMany
	eoSelectMany<EoType> select(selectOne, parameter.offspring_size, eo_is_an_integer);

	// and the generational replacement
    	//eoGenerationalReplacement<EoType> replace;
	// or the SteadtState replacment
	//eoSSGAWorseReplacement<EoType> replace;
	// or comma selection
	eoCommaReplacement<EoType> replace;

    	// Terminators
    	eoGenContinue<EoType> term(parameter.nGenerations);

    	eoCheckPoint<EoType> checkPoint(term);

	// STATISTICS
    	eoAverageStat<EoType>     avg;
    	eoBestFitnessStat<EoType> best;


    	// Add it to the checkpoint,
    	// so the counter is updated (here, incremented) every generation
    	checkPoint.add(increment);
	checkPoint.add(avg);
	checkPoint.add(best);

#ifdef HAVE_GNUPLOT
	eoGnuplot1DMonitor gnuplotmonitor("gnuplotBestStats");
  	gnuplotmonitor.add(generationCounter);
	gnuplotmonitor.add(best);
	// we need to add a empty string variable if we want to seed the second fitness value
	eoValueParam<string> dummy1("", "Smallest Tree Size");
	gnuplotmonitor.add(dummy1);

	eoGnuplot1DMonitor gnuplotAvgmonitor("gnuplotAvgStats");
	gnuplotAvgmonitor.add(generationCounter);
	gnuplotAvgmonitor.add(avg);
	// we need to add a empty string variable if we want to seed the second fitness value
	eoValueParam<string> dummy2("", "Average Tree Size");
	gnuplotAvgmonitor.add(dummy2);

	checkPoint.add(gnuplotmonitor);
  	checkPoint.add(gnuplotAvgmonitor);
#endif
	// GP Generation
	eoEasyEA<EoType> gp(checkPoint, eval, select, transform, replace);

    	cout << "Initialization done" << endl;


    	try
    	{
      		gp(pop);
    	}
    	catch (exception& e)
    	{
	    cout << "exception: " << e.what() << endl;;
	    exit(EXIT_FAILURE);
    	}

    	return 1;

};