/**
* Constructs a new NeatAlgorithm.
*/
NeatAlgorithm::NeatAlgorithm(World *world)
{
if(world == 0) {
return;
}
NeatEvolutionAlgorithm *neatAlg = new NeatEvolutionAlgorithm();
world->setEvolutionAlgorithm(neatAlg);
//Add Selection Methods and genotypePhenotypeMapper
QList<Population*> populations = world->getPopulations();
for(QListIterator<Population*> i(populations); i.hasNext();) {
Population *population = i.next();
//Add Selection Methods.
NeatSelectionMethod *selection = new NeatSelectionMethod();
population->addSelectionMethod(selection);
selection->getPopulationProportion()->set(1.0);
selection->setResponsibleFitnessFunction(population->getFitnessFunctions().at(0));
//Add GenotypePhenotypeMapper.
NeatGenotypePhenotypeMapper *mapper = new NeatGenotypePhenotypeMapper();
population->setGenotypePhenotypeMapper(mapper);
}
}
bool EvolutionOperatorTestApplication::buildEvolutionSystem() {
Evolution::install();
//install evolution system with local simulator evolution.
new NeuroEvolutionSelector(new LocalNetworkInSimulationEvaluationMethod());
if(!Evolution::getEvolutionManager()->getEvolutionWorlds().empty()) {
World *world = Evolution::getEvolutionManager()->getEvolutionWorlds().at(0);
const QList<Population*> &populations = world->getPopulations();
for(QListIterator<Population*> i(populations); i.hasNext();) {
Population *population = i.next();
//Add Selection Methods.
FirstParentsTestSelectionMethod *firstParentSelection = new FirstParentsTestSelectionMethod();
population->addSelectionMethod(firstParentSelection);
firstParentSelection->getPopulationProportion()->set(0.0);
firstParentSelection->setResponsibleFitnessFunction(population->getFitnessFunctions().at(0));
}
}
return true;
}
bool JanEvolution::buildEvolutionSystem() {
World *world = new World("Main");
Population *population = new Population("HumanoidControllers");
world->addPopulation(population);
IdentityGenotypePhenotypeMapper *mapper = new IdentityGenotypePhenotypeMapper();
population->setGenotypePhenotypeMapper(mapper);
new ENS3EvolutionAlgorithm(world);
world->setEvaluationMethod(new LocalNetworkInSimulationEvaluationMethod());
Evolution::getEvolutionManager()->addEvolutionWorld(world);
//Add statistics calculator.
Statistics::getStatisticsManager()->addGenerationStatistics(
new BasicNeuralNetworkStatistics(*population));
FitnessFunction *fitness = 0;
CommandLineArgument *fitnessFunctionArg = new CommandLineArgument(
"fitness", "fit", "<prototypeName> <fitnessFunctionName>",
"Creates a copy of <prototypeName> and uses it for the population"
" with the given <fitnessFunctionName>.", 2, 0, true);
QList<QString> fitArguments = fitnessFunctionArg->getEntryParameters(0);
if(fitArguments.size() > 1) {
fitness = Fitness::getFitnessManager()
->createFitnessFunctionFromPrototype(fitArguments.at(0), fitArguments.at(1));
if(fitness == 0) {
cerr << "Failed to create FitnessFunction prototype ["
<< fitArguments.at(0).toStdString().c_str() << endl;
}
}
if(fitness == 0) {
fitness = Fitness::getFitnessManager()
->createFitnessFunctionFromPrototype("Script", "Script");
}
population->addFitnessFunction(fitness);
TournamentSelectionMethod *tournament = new TournamentSelectionMethod(5);
PoissonDistributionRanking *poissonDistribution = new PoissonDistributionRanking();
population->addSelectionMethod(tournament);
population->addSelectionMethod(poissonDistribution);
tournament->setResponsibleFitnessFunction(fitness);
poissonDistribution->setResponsibleFitnessFunction(fitness);
poissonDistribution->getPopulationProportion()->set(0.0);
//add individual statistics
StandardIndividualStatistics indStatistics(population);
NeuralNetworkIndividualStatistics neuroStatistics(population);
return true;
}
/**
* Note. This constructore assumes that world is fully configured.
* The correct number of populations has already to be set..
* Also a FitnessFunction has to be set for each population before this constructor
* is called. The first FitnessFunction in the list of FitnessFunctions
* of each population is used as responsible FitnessFunction for the SelectionMethods.
*
* ENS3 consists of:
* - the ManipulationChainAlgorithm with a number of mutation operators.
* - the IdentityPhenotypeGenotypeMapper.
* - a number of compatible SelectionMethods with the PoissionDistribution as default.
*/
ENS3EvolutionAlgorithm::ENS3EvolutionAlgorithm(World *world)
{
NeuralNetworkManipulationChainAlgorithm *evo =
new NeuralNetworkManipulationChainAlgorithm("ENS3");
if(world != 0) {
world->setEvolutionAlgorithm(evo);
}
CreateNetworkOperator *createNetOp =
new CreateNetworkOperator("CreateInitNetwork");
CloneNetworkOperator *cloneNetOp =
new CloneNetworkOperator("CloneParent");
RemoveNeuronOperator *removeNeuronOp =
new RemoveNeuronOperator("RemoveNeurons");
RemoveSynapseOperator *removeSynapseOp =
new RemoveSynapseOperator("RemoveSynapse");
RemoveBiasOperator *removeBiasOp =
new RemoveBiasOperator("RemoveBias");
InsertNeuronOperator *insertNeuronOp =
new InsertNeuronOperator("InsertNeuron");
InsertSynapseOperator *insertSynapseOp =
new InsertSynapseOperator("InsertSynapse");
InsertBiasOperator *insertBiasOp =
new InsertBiasOperator("InsertBias");
InitializeSynapsesOperator *initSynapsesOp =
new InitializeSynapsesOperator("InitSynapses");
InitializeBiasOperator *initBiasOp =
new InitializeBiasOperator("InitBias");
ChangeBiasOperator *changeBias =
new ChangeBiasOperator("ChangeBias");
ChangeSynapseStrengthOperator *changeSynapseStrengthOp =
new ChangeSynapseStrengthOperator("ChangeSynapseStrength");
// ConnectNeuronClassesFilter *connectNeuronClassFilter =
// new ConnectNeuronClassesFilter("ConnectNeuronClasses");
EnableSynapseOperator *enableSynapseOperator =
new EnableSynapseOperator("EnableSynapse", true);
EnableSynapseOperator *disableSynapseOperator =
new EnableSynapseOperator("DisableSynapse", false);
evo->addOperator(createNetOp);
evo->addOperator(cloneNetOp);
evo->addOperator(removeNeuronOp);
evo->addOperator(removeSynapseOp);
evo->addOperator(removeBiasOp);
evo->addOperator(insertNeuronOp);
evo->addOperator(insertSynapseOp);
evo->addOperator(insertBiasOp);
evo->addOperator(initSynapsesOp);
evo->addOperator(enableSynapseOperator);
evo->addOperator(disableSynapseOperator);
evo->addOperator(initBiasOp);
evo->addOperator(changeBias);
evo->addOperator(changeSynapseStrengthOp);
// evo->addOperator(connectNeuronClassFilter);
createNetOp->getOperatorIndexValue()->set(0);
cloneNetOp->getOperatorIndexValue()->set(5);
removeNeuronOp->getOperatorIndexValue()->set(10);
removeSynapseOp->getOperatorIndexValue()->set(15);
removeBiasOp->getOperatorIndexValue()->set(17);
insertNeuronOp->getOperatorIndexValue()->set(20);
insertSynapseOp->getOperatorIndexValue()->set(30);
insertBiasOp->getOperatorIndexValue()->set(40);
initSynapsesOp->getOperatorIndexValue()->set(50);
initBiasOp->getOperatorIndexValue()->set(52);
disableSynapseOperator->getOperatorIndexValue()->set(54);
enableSynapseOperator->getOperatorIndexValue()->set(55);
changeBias->getOperatorIndexValue()->set(60);
changeSynapseStrengthOp->getOperatorIndexValue()->set(70);
// connectNeuronClassFilter->getOperatorIndexValue()->set(1100);
//TODO remove (is not ENS3)
// ResolveConstraintsOperator *constraintResolver =
// new ResolveConstraintsOperator("ConstraintResolver");
// constraintResolver->getOperatorIndexValue()->set(1000);
// evo->addOperator(constraintResolver);
//Add Selection Methods and genotypePhenotypeMapper
QList<Population*> populations = world->getPopulations();
for(QListIterator<Population*> i(populations); i.hasNext();) {
Population *population = i.next();
//Add Selection Methods.
TournamentSelectionMethod *tournament = new TournamentSelectionMethod(5);
PoissonDistributionRanking *poissonDistribution = new PoissonDistributionRanking();
population->addSelectionMethod(tournament);
population->addSelectionMethod(poissonDistribution);
tournament->getPopulationProportion()->set(0.0);
poissonDistribution->getPopulationProportion()->set(1.0);
tournament->setResponsibleFitnessFunction(population->getFitnessFunctions().at(0));
poissonDistribution->setResponsibleFitnessFunction(population->getFitnessFunctions().at(0));
//Add GenotypePhenotypeMapper.
IdentityGenotypePhenotypeMapper *mapper = new IdentityGenotypePhenotypeMapper();
population->setGenotypePhenotypeMapper(mapper);
}
}
/**
* Constructs a new ModularNeuroEvolution1.
*/
ModularNeuroEvolution1::ModularNeuroEvolution1(World *world)
{
NeuralNetworkManipulationChainAlgorithm *evo =
new NeuralNetworkManipulationChainAlgorithm("ICONE");
evo->setRequiredNumberOfParentsPerIndividual(2);
if(world != 0) {
world->setEvolutionAlgorithm(evo);
}
CreateNetworkOperator *createNetOp =
new CreateNetworkOperator("CreateInitNetwork");
ModuleCrossOverOperator *modularCrossover =
new ModuleCrossOverOperator("ModularCrossover");
CloneNetworkOperator *cloneNetOp =
new CloneNetworkOperator("CloneParent");
RemoveNeuronOperator *removeNeuronOp =
new RemoveNeuronOperator("RemoveNeurons");
RemoveSynapseOperator *removeSynapseOp =
new RemoveSynapseOperator("RemoveSynapse");
RemoveBiasOperator *removeBiasOp =
new RemoveBiasOperator("RemoveBias");
InsertNeuroModuleOperator *insertNeuroModule =
new InsertNeuroModuleOperator("InsertNeuroModule");
InsertNeuronOperator *insertNeuronOp =
new InsertNeuronOperator("InsertNeuron");
InsertSynapseModularOperator *insertSynapseOp =
new InsertSynapseModularOperator("InsertSynapse");
InsertBiasOperator *insertBiasOp =
new InsertBiasOperator("InsertBias");
InitializeSynapsesOperator *initSynapsesOp =
new InitializeSynapsesOperator("InitSynapses");
InitializeBiasOperator *initBiasOp =
new InitializeBiasOperator("InitBias");
ChangeBiasOperator *changeBias =
new ChangeBiasOperator("ChangeBias");
ChangeSynapseStrengthOperator *changeSynapseStrengthOp =
new ChangeSynapseStrengthOperator("ChangeSynapseStrength");
AdaptSRNParametersOperator *adaptSRNParametersOperator =
new AdaptSRNParametersOperator("AdaptSRNParameters");
EnableSynapseOperator *enableSynapseOperator =
new EnableSynapseOperator("EnableSynapse", true);
EnableSynapseOperator *disableSynapseOperator =
new EnableSynapseOperator("DisableSynapse", false);
ResolveConstraintsOperator *constraintResolver =
new ResolveConstraintsOperator("ConstraintResolver");
ConnectNeuronClassesFilter *connectNeuronClassFilter =
new ConnectNeuronClassesFilter("ConnectNeuronClasses");
evo->addOperator(createNetOp);
evo->addOperator(modularCrossover);
evo->addOperator(cloneNetOp);
evo->addOperator(removeNeuronOp);
evo->addOperator(removeSynapseOp);
evo->addOperator(removeBiasOp);
evo->addOperator(insertNeuroModule);
evo->addOperator(insertNeuronOp);
evo->addOperator(insertSynapseOp);
evo->addOperator(insertBiasOp);
evo->addOperator(initSynapsesOp);
evo->addOperator(enableSynapseOperator);
evo->addOperator(disableSynapseOperator);
evo->addOperator(initBiasOp);
evo->addOperator(changeBias);
evo->addOperator(adaptSRNParametersOperator);
evo->addOperator(changeSynapseStrengthOp);
evo->addOperator(connectNeuronClassFilter);
createNetOp->getOperatorIndexValue()->set(0);
modularCrossover->getOperatorIndexValue()->set(10);
cloneNetOp->getOperatorIndexValue()->set(20);
removeNeuronOp->getOperatorIndexValue()->set(30);
removeSynapseOp->getOperatorIndexValue()->set(40);
removeBiasOp->getOperatorIndexValue()->set(50);
insertNeuroModule->getOperatorIndexValue()->set(60);
insertNeuronOp->getOperatorIndexValue()->set(70);
insertSynapseOp->getOperatorIndexValue()->set(80);
insertBiasOp->getOperatorIndexValue()->set(90);
initSynapsesOp->getOperatorIndexValue()->set(100);
initBiasOp->getOperatorIndexValue()->set(120);
disableSynapseOperator->getOperatorIndexValue()->set(140);
enableSynapseOperator->getOperatorIndexValue()->set(160);
changeBias->getOperatorIndexValue()->set(180);
changeSynapseStrengthOp->getOperatorIndexValue()->set(200);
adaptSRNParametersOperator->getOperatorIndexValue()->set(220);
constraintResolver->getOperatorIndexValue()->set(1000);
connectNeuronClassFilter->getOperatorIndexValue()->set(1100);
evo->addOperator(constraintResolver);
modularCrossover->getEnableOperatorValue()->set(false);
enableSynapseOperator->getEnableOperatorValue()->set(false);
disableSynapseOperator->getEnableOperatorValue()->set(false);
modularCrossover->getHiddenValue()->set(true);
enableSynapseOperator->getHiddenValue()->set(true);
disableSynapseOperator->getHiddenValue()->set(true);
//Add Selection Methods and genotypePhenotypeMapper
QList<Population*> populations = world->getPopulations();
for(QListIterator<Population*> i(populations); i.hasNext();) {
Population *population = i.next();
//Add Selection Methods.
TournamentSelectionMethod *tournament = new TournamentSelectionMethod(5);
StochasticUniversalSamplingSelection *universalSampling = new StochasticUniversalSamplingSelection();
MultiObjectiveTournamentSelection *multiObjectivTournament = new MultiObjectiveTournamentSelection(5);
PoissonDistributionRanking *poissonDistribution = new PoissonDistributionRanking();
population->addSelectionMethod(tournament);
population->addSelectionMethod(universalSampling);
population->addSelectionMethod(multiObjectivTournament);
population->addSelectionMethod(poissonDistribution);
tournament->getPopulationProportion()->set(1.0);
universalSampling->getPopulationProportion()->set(0.0);
multiObjectivTournament->getPopulationProportion()->set(0.0);
poissonDistribution->getPopulationProportion()->set(0.0);
tournament->setResponsibleFitnessFunction(population->getFitnessFunctions().at(0));
universalSampling->setResponsibleFitnessFunction(population->getFitnessFunctions().at(0));
multiObjectivTournament->setResponsibleFitnessFunction(population->getFitnessFunctions().at(0));
poissonDistribution->setResponsibleFitnessFunction(population->getFitnessFunctions().at(0));
//Add GenotypePhenotypeMapper.
IdentityGenotypePhenotypeMapper *mapper = new IdentityGenotypePhenotypeMapper();
population->setGenotypePhenotypeMapper(mapper);
}
}
