134 lines
4.2 KiB
C++
134 lines
4.2 KiB
C++
// Program to test several EO-ES features
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#ifdef _MSC_VER
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#pragma warning(disable:4786)
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#endif
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#include <algorithm>
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#include <string>
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#include <iostream>
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#include <iterator>
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#include <stdexcept>
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#include <time.h>
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using namespace std;
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#include <eo>
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// representation specific
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#include <es/evolution_strategies>
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#include "real_value.h" // the sphere fitness
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// Now the main
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///////////////
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typedef eoMinimizingFitness FitT;
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template <class EOT>
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void runAlgorithm(EOT, eoParser& _parser, eoState& _state, eoEsObjectiveBounds& _bounds);
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int main(int argc, char *argv[])
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{
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// Create the command-line parser
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eoParser parser( argc, argv, "Basic EA for vector<float> with adaptive mutations");
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// Define Parameters and load them
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eoValueParam<uint32>& seed = parser.createParam(static_cast<uint32>(time(0)), "seed", "Random number seed");
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eoValueParam<string>& load_name = parser.createParam(string(), "Load","Load a state file",'L');
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eoValueParam<string>& save_name = parser.createParam(string(), "Save","Saves a state file",'S');
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eoValueParam<bool>& stdevs = parser.createParam(false, "Stdev", "Use adaptive mutation rates", 's');
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eoValueParam<bool>& corr = parser.createParam(false, "Correl", "Use correlated mutations", 'c');
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eoValueParam<unsigned>& chromSize = parser.createParam(unsigned(50), "ChromSize", "Number of chromosomes", 'n');
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eoValueParam<double>& minimum = parser.createParam(-1.e5, "Min", "Minimum for Objective Variables", 'l');
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eoValueParam<double>& maximum = parser.createParam(1.e5, "Max", "Maximum for Objective Variables", 'h');
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eoState state;
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state.registerObject(parser);
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rng.reseed(seed.value());
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if (!load_name.value().empty())
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{ // load the parser. This is only neccessary when the user wants to
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// be able to change the parameters in the state file by hand
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// Note that only parameters inserted in the parser at this point
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// will be loaded!.
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state.load(load_name.value()); // load the parser
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}
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state.registerObject(rng);
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eoEsObjectiveBounds bounds(chromSize.value(), minimum.value(), maximum.value());
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// Run the appropriate algorithm
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if (stdevs.value() == false && corr.value() == false)
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{
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runAlgorithm(eoEsSimple<FitT>() ,parser, state, bounds);
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}
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else if (corr.value() == true)
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{
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runAlgorithm(eoEsFull<FitT>(),parser, state, bounds);
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}
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else
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{
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runAlgorithm(eoEsStdev<FitT>(), parser, state, bounds);
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}
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// and save
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if (!save_name.value().empty())
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{
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string file_name = save_name.value();
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save_name.value() = ""; // so that it does not appear in the parser section of the state file
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state.save(file_name);
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}
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return 0;
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}
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template <class EOT>
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void runAlgorithm(EOT, eoParser& _parser, eoState& _state, eoEsObjectiveBounds& _bounds)
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{
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// evaluation
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eoEvalFuncPtr<EOT, double, const vector<double>&> eval( real_value );
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// population parameters, unfortunately these can not be altered in the state file
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eoValueParam<unsigned> mu = _parser.createParam(unsigned(50), "mu","Size of the population");
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eoValueParam<float>lambda_rate = _parser.createParam(float(7.0), "lambda_rate", "Factor of children to produce");
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if (lambda_rate.value() < 1.0f)
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{
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throw logic_error("lambda_rate must be larger than 1 in a comma strategy");
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}
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// Initialization
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eoEsChromInit<EOT> init(_bounds);
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eoPop<EOT>& pop = _state.takeOwnership(eoPop<EOT>(mu.value(), init));
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_state.registerObject(pop);
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// evaluate initial population
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apply<EOT>(eval, pop);
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// Ok, time to set up the algorithm
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// Proxy for the mutation parameters
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eoEsMutationInit mutateInit(_parser);
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eoEsMutate<EOT> mutate(mutateInit, _bounds);
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// monitoring, statistics etc.
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eoAverageStat<EOT> average;
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eoStdoutMonitor monitor;
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monitor.add(average);
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eoGenContinue<EOT> cnt(2000);
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eoCheckPoint<EOT> checkpoint(cnt);
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checkpoint.add(monitor);
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checkpoint.add(average);
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eoProportionalGOpSel<EOT> opSel;
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opSel.addOp(mutate, 1.0);
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eoEvolutionStrategy<EOT> es(checkpoint, eval, opSel, lambda_rate.value(), eoEvolutionStrategy<EOT>::comma_strategy());
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es(pop);
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}
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