329 lines
12 KiB
C++
329 lines
12 KiB
C++
//-----------------------------------------------------------------------------
|
|
// SecondRealEA.cpp
|
|
//-----------------------------------------------------------------------------
|
|
//*
|
|
// Same code than FirstBitEA as far as Evolutionary Computation is concerned
|
|
// but now you learn to enter the parameters in a more flexible way
|
|
// (also slightly different than in SecondBitEA.cpp)
|
|
// and to twidle the output to your preferences (as in SecondBitEA.cpp)
|
|
//
|
|
//-----------------------------------------------------------------------------
|
|
#ifdef HAVE_CONFIG_H
|
|
#include <config.h>
|
|
#endif
|
|
|
|
// standard includes
|
|
#include <fstream>
|
|
#include <iostream> // cout
|
|
#include <stdexcept> // runtime_error
|
|
|
|
// the general include for eo
|
|
#include <eo>
|
|
#include <es.h>
|
|
|
|
// REPRESENTATION
|
|
//-----------------------------------------------------------------------------
|
|
// define your individuals
|
|
typedef eoReal<eoMinimizingFitness> Indi;
|
|
|
|
// Use functions from namespace std
|
|
using namespace std;
|
|
|
|
// EVALFUNC
|
|
//-----------------------------------------------------------------------------
|
|
// a simple fitness function that computes the euclidian norm of a real vector
|
|
// Now in a separate file, and declared as binary_value(const vector<bool> &)
|
|
|
|
#include "real_value.h"
|
|
|
|
// GENERAL
|
|
//-----------------------------------------------------------------------------
|
|
|
|
void main_function(int argc, char **argv)
|
|
{
|
|
// PARAMETRES
|
|
//-----------------------------------------------------------------------------
|
|
// instead of having all values of useful parameters as constants, read them:
|
|
// either on the command line (--option=value or -o=value)
|
|
// or in a parameter file (same syntax, order independent,
|
|
// # = usual comment character
|
|
// or in the environment (TODO)
|
|
|
|
// First define a parser from the command-line arguments
|
|
eoParser parser(argc, argv);
|
|
|
|
// For each parameter, you can in on single line
|
|
// define the parameter, read it through the parser, and assign it
|
|
|
|
unsigned seed = parser.createParam(unsigned(time(0)), "seed", "Random number seed", 'S').value(); // will be in default section General
|
|
|
|
// description of genotype
|
|
unsigned vecSize = parser.createParam(unsigned(8), "vecSize", "Genotype size",'V', "Representation" ).value();
|
|
|
|
// parameters for evolution engine
|
|
unsigned popSize = parser.createParam(unsigned(10), "popSize", "Population size",'P', "Evolution engine" ).value();
|
|
|
|
unsigned tSize = parser.createParam(unsigned(2), "tSize", "Tournament size",'T', "Evolution Engine" ).value();
|
|
|
|
// init and stop
|
|
string loadName = parser.createParam(string(""), "Load","A save file to restart from",'L', "Persistence" ).value();
|
|
|
|
unsigned maxGen = parser.createParam(unsigned(100), "maxGen", "Maximum number of generations",'G', "Stopping criterion" ).value();
|
|
|
|
unsigned minGen = parser.createParam(unsigned(100), "minGen", "Minimum number of generations",'g', "Stopping criterion" ).value();
|
|
|
|
unsigned steadyGen = parser.createParam(unsigned(100), "steadyGen", "Number of generations with no improvement",'s', "Stopping criterion" ).value();
|
|
|
|
// operators probabilities at the algorithm level
|
|
double pCross = parser.createParam(double(0.6), "pCross", "Probability of Crossover", 'C', "Genetic Operators" ).value();
|
|
|
|
double pMut = parser.createParam(double(0.1), "pMut", "Probability of Mutation", 'M', "Genetic Operators" ).value();
|
|
|
|
// relative rates for crossovers
|
|
double hypercubeRate = parser.createParam(double(1), "hypercubeRate", "Relative rate for hypercube crossover", '\0', "Genetic Operators" ).value();
|
|
|
|
double segmentRate = parser.createParam(double(1), "segmentRate", "Relative rate for segment crossover", '\0', "Genetic Operators" ).value();
|
|
|
|
// internal parameters for the mutations
|
|
double EPSILON = parser.createParam(double(0.01), "EPSILON", "Width for uniform mutation", '\0', "Genetic Operators" ).value();
|
|
|
|
double SIGMA = parser.createParam(double(0.3), "SIGMA", "Sigma for normal mutation", '\0', "Genetic Operators" ).value();
|
|
|
|
// relative rates for mutations
|
|
double uniformMutRate = parser.createParam(double(1), "uniformMutRate", "Relative rate for uniform mutation", '\0', "Genetic Operators" ).value();
|
|
|
|
double detMutRate = parser.createParam(double(1), "detMutRate", "Relative rate for det-uniform mutation", '\0', "Genetic Operators" ).value();
|
|
|
|
double normalMutRate = parser.createParam(double(1), "normalMutRate", "Relative rate for normal mutation", '\0', "Genetic Operators" ).value();
|
|
|
|
// the name of the "status" file where all actual parameter values will be saved
|
|
string str_status = parser.ProgramName() + ".status"; // default value
|
|
string statusName = parser.createParam(str_status, "status","Status file",'S', "Persistence" ).value();
|
|
|
|
// do the following AFTER ALL PARAMETERS HAVE BEEN PROCESSED
|
|
// i.e. in case you need parameters somewhere else, postpone these
|
|
if (parser.userNeedsHelp())
|
|
{
|
|
parser.printHelp(cout);
|
|
exit(1);
|
|
}
|
|
if (statusName != "")
|
|
{
|
|
ofstream os(statusName.c_str());
|
|
os << parser; // and you can use that file as parameter file
|
|
}
|
|
|
|
// EVAL
|
|
/////////////////////////////
|
|
// Fitness function
|
|
////////////////////////////
|
|
// Evaluation: from a plain C++ fn to an EvalFunc Object
|
|
// you need to give the full description of the function
|
|
eoEvalFuncPtr<Indi, double, const vector<double>& > plainEval( real_value );
|
|
// ... to an object that counts the nb of actual evaluations
|
|
eoEvalFuncCounter<Indi> eval(plainEval);
|
|
|
|
// INIT
|
|
////////////////////////////////
|
|
// Initilisation of population
|
|
////////////////////////////////
|
|
// Either load or initialize
|
|
// create an empty pop
|
|
eoPop<Indi> pop;
|
|
// create a state for reading
|
|
eoState inState; // a state for loading - WITHOUT the parser
|
|
// register the rng and the pop in the state, so they can be loaded,
|
|
// and the present run will be the exact conitnuation of the saved run
|
|
// eventually with different parameters
|
|
inState.registerObject(rng);
|
|
inState.registerObject(pop);
|
|
|
|
if (loadName != "")
|
|
{
|
|
inState.load(loadName); // load the pop and the rng
|
|
// the fitness is read in the file:
|
|
// do only evaluate the pop if the fitness has changed
|
|
}
|
|
else
|
|
{
|
|
rng.reseed(seed);
|
|
// a Indi random initializer
|
|
// based on boolean_generator class (see utils/rnd_generator.h)
|
|
eoUniformGenerator<double> uGen(-1.0, 1.0);
|
|
eoInitFixedLength<Indi> random(vecSize, uGen);
|
|
|
|
// Init pop from the randomizer: need to use the append function
|
|
pop.append(popSize, random);
|
|
// and evaluate pop (STL syntax)
|
|
apply<Indi>(eval, pop);
|
|
} // end of initializatio of the population
|
|
|
|
// OUTPUT
|
|
// sort pop before printing it!
|
|
pop.sort();
|
|
// Print (sorted) intial population (raw printout)
|
|
cout << "Initial Population" << endl;
|
|
cout << pop;
|
|
|
|
// ENGINE
|
|
/////////////////////////////////////
|
|
// selection and replacement
|
|
////////////////////////////////////
|
|
// SELECT
|
|
// The robust tournament selection
|
|
eoDetTournamentSelect<Indi> selectOne(tSize);
|
|
// is now encapsulated in a eoSelectPerc (entage)
|
|
eoSelectPerc<Indi> select(selectOne);// by default rate==1
|
|
|
|
// REPLACE
|
|
// And we now have the full slection/replacement - though with
|
|
// no replacement (== generational replacement) at the moment :-)
|
|
eoGenerationalReplacement<Indi> replace;
|
|
|
|
// OPERATORS
|
|
//////////////////////////////////////
|
|
// The variation operators
|
|
//////////////////////////////////////
|
|
// CROSSOVER
|
|
// uniform chooce on segment made by the parents
|
|
eoSegmentCrossover<Indi> xoverS;
|
|
// uniform choice in hypercube built by the parents
|
|
eoHypercubeCrossover<Indi> xoverA;
|
|
// Combine them with relative weights
|
|
eoPropCombinedQuadOp<Indi> xover(xoverS, segmentRate);
|
|
xover.add(xoverA, hypercubeRate, true);
|
|
|
|
// MUTATION
|
|
// offspring(i) uniformly chosen in [parent(i)-epsilon, parent(i)+epsilon]
|
|
eoUniformMutation<Indi> mutationU(EPSILON);
|
|
// k (=1) coordinates of parents are uniformly modified
|
|
eoDetUniformMutation<Indi> mutationD(EPSILON);
|
|
// all coordinates of parents are normally modified (stDev SIGMA)
|
|
eoNormalMutation<Indi> mutationN(SIGMA);
|
|
// Combine them with relative weights
|
|
eoPropCombinedMonOp<Indi> mutation(mutationU, uniformMutRate);
|
|
mutation.add(mutationD, detMutRate);
|
|
mutation.add(mutationN, normalMutRate, true);
|
|
|
|
// The operators are encapsulated into an eoTRansform object
|
|
eoSGATransform<Indi> transform(xover, pCross, mutation, pMut);
|
|
|
|
// STOP
|
|
//////////////////////////////////////
|
|
// termination condition see FirstBitEA.cpp
|
|
/////////////////////////////////////
|
|
eoGenContinue<Indi> genCont(maxGen);
|
|
eoSteadyFitContinue<Indi> steadyCont(minGen, steadyGen);
|
|
eoFitContinue<Indi> fitCont(0);
|
|
eoCombinedContinue<Indi> continuator(genCont);
|
|
continuator.add(steadyCont);
|
|
continuator.add(fitCont);
|
|
|
|
|
|
// CHECKPOINT
|
|
// but now you want to make many different things every generation
|
|
// (e.g. statistics, plots, ...).
|
|
// the class eoCheckPoint is dedicated to just that:
|
|
|
|
// Declare a checkpoint (from a continuator: an eoCheckPoint
|
|
// IS AN eoContinue and will be called in the loop of all algorithms)
|
|
eoCheckPoint<Indi> checkpoint(continuator);
|
|
|
|
// Create a counter parameter
|
|
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());
|
|
|
|
// Add it to the checkpoint,
|
|
// so the counter is updated (here, incremented) every generation
|
|
checkpoint.add(increment);
|
|
|
|
// now some statistics on the population:
|
|
// Best fitness in population
|
|
eoBestFitnessStat<Indi> bestStat;
|
|
// Second moment stats: average and stdev
|
|
eoSecondMomentStats<Indi> SecondStat;
|
|
|
|
// Add them to the checkpoint to get them called at the appropriate time
|
|
checkpoint.add(bestStat);
|
|
checkpoint.add(SecondStat);
|
|
|
|
// The Stdout monitor will print parameters to the screen ...
|
|
eoStdoutMonitor monitor(false);
|
|
|
|
// when called by the checkpoint (i.e. at every generation)
|
|
checkpoint.add(monitor);
|
|
|
|
// the monitor will output a series of parameters: add them
|
|
monitor.add(generationCounter);
|
|
monitor.add(eval); // because now eval is an eoEvalFuncCounter!
|
|
monitor.add(bestStat);
|
|
monitor.add(SecondStat);
|
|
|
|
// A file monitor: will print parameters to ... a File, yes, you got it!
|
|
eoFileMonitor fileMonitor("stats.xg", " ");
|
|
|
|
// the checkpoint mechanism can handle multiple monitors
|
|
checkpoint.add(fileMonitor);
|
|
|
|
// the fileMonitor can monitor parameters, too, but you must tell it!
|
|
fileMonitor.add(generationCounter);
|
|
fileMonitor.add(bestStat);
|
|
fileMonitor.add(SecondStat);
|
|
|
|
// Last type of item the eoCheckpoint can handle: state savers:
|
|
eoState outState;
|
|
// Register the algorithm into the state (so it has something to save!!)
|
|
outState.registerObject(parser);
|
|
outState.registerObject(pop);
|
|
outState.registerObject(rng);
|
|
|
|
// and feed the state to state savers
|
|
// save state every 100th generation
|
|
eoCountedStateSaver stateSaver1(20, outState, "generation");
|
|
// save state every 1 seconds
|
|
eoTimedStateSaver stateSaver2(1, outState, "time");
|
|
|
|
// Don't forget to add the two savers to the checkpoint
|
|
checkpoint.add(stateSaver1);
|
|
checkpoint.add(stateSaver2);
|
|
// and that's it for the (control and) output
|
|
|
|
// GENERATION
|
|
/////////////////////////////////////////
|
|
// the algorithm
|
|
////////////////////////////////////////
|
|
|
|
// Easy EA requires
|
|
// stopping criterion, eval, selection, transformation, replacement
|
|
eoEasyEA<Indi> gga(checkpoint, eval, select, transform, replace);
|
|
|
|
// Apply algo to pop - that's it!
|
|
gga(pop);
|
|
|
|
// OUTPUT
|
|
// Print (sorted) intial population
|
|
pop.sort();
|
|
cout << "FINAL Population\n" << pop << endl;
|
|
// GENERAL
|
|
}
|
|
|
|
// A main that catches the exceptions
|
|
|
|
int main(int argc, char **argv)
|
|
{
|
|
try
|
|
{
|
|
main_function(argc, argv);
|
|
}
|
|
catch(exception& e)
|
|
{
|
|
cout << "Exception: " << e.what() << '\n';
|
|
}
|
|
|
|
return 1;
|
|
}
|