NEAT::GeneticPopulation* CoCheckersExperiment::createInitialPopulation(int populationSize)
{
GeneticPopulation *population = new GeneticPopulation(
shared_ptr<CoCheckersExperiment>((CoCheckersExperiment*)this->clone())
);
vector<GeneticNodeGene> genes;
genes.push_back(GeneticNodeGene("Bias","NetworkSensor",0,false));
genes.push_back(GeneticNodeGene("X1","NetworkSensor",0,false));
genes.push_back(GeneticNodeGene("Y1","NetworkSensor",0,false));
genes.push_back(GeneticNodeGene("X2","NetworkSensor",0,false));
genes.push_back(GeneticNodeGene("Y2","NetworkSensor",0,false));
genes.push_back(GeneticNodeGene("DeltaX","NetworkSensor",0,false));
genes.push_back(GeneticNodeGene("DeltaY","NetworkSensor",0,false));
genes.push_back(GeneticNodeGene("Output_ab","NetworkOutputNode",1,false,ACTIVATION_FUNCTION_SIGMOID));
genes.push_back(GeneticNodeGene("Output_bc","NetworkOutputNode",1,false,ACTIVATION_FUNCTION_SIGMOID));
genes.push_back(GeneticNodeGene("Output_ac","NetworkOutputNode",1,false,ACTIVATION_FUNCTION_SIGMOID));
#if CHECKERS_EXPERIMENT_ENABLE_BIASES
genes.push_back(GeneticNodeGene("Bias_b","NetworkOutputNode",1,false,ACTIVATION_FUNCTION_SIGMOID));
genes.push_back(GeneticNodeGene("Bias_c","NetworkOutputNode",1,false,ACTIVATION_FUNCTION_SIGMOID));
#endif
for (int a=0;a<populationSize;a++)
{
shared_ptr<GeneticIndividual> individual(new GeneticIndividual(genes,true,1.0));
for (int b=0;b<0;b++)
{
individual->testMutate();
}
population->addIndividual(individual);
}
shared_ptr<NEAT::CoEvoGeneticGeneration> coEvoGeneration =
static_pointer_cast<NEAT::CoEvoGeneticGeneration>(population->getGeneration());
//Create the tests
for (int a=0;a<(population->getIndividualCount()/10);a++)
{
shared_ptr<NEAT::GeneticIndividual> individual(new GeneticIndividual(genes,true,1.0));
//This function clones the individual to make a test
coEvoGeneration->addTest(individual);
}
coEvoGeneration->bootstrap();
cout << "Finished creating population\n";
return population;
}
GeneticPopulation* ModNeatExperiment7::createInitialPopulation(int populationSize) {
GeneticPopulation *population = new GeneticPopulation();
vector<GeneticNodeGene> genes;
// Set-up the CCPPN which encodes the substrate weights
////// CCPPN encoding a 3 layered sandwich substrate's weights
// Configuration of the CCPPN's Input layer
genes.push_back(GeneticNodeGene("X1", "NetworkSensor", 0, false)); // position on the X axis in the substrate's link start layers
genes.push_back(GeneticNodeGene("Y1", "NetworkSensor", 0, false)); // position on the Y axis in the substrate's link start layers
genes.push_back(GeneticNodeGene("Z1", "NetworkSensor", 0, false)); // position on the Z axis in the substrate's link start layers
genes.push_back(GeneticNodeGene("X2", "NetworkSensor", 0, false)); // position on the X axis in the substrate's link end layers
genes.push_back(GeneticNodeGene("Y2", "NetworkSensor", 0, false)); // position on the Y axis in the substrate's link end layers
genes.push_back(GeneticNodeGene("Z2", "NetworkSensor", 0, false)); // position on the Z axis in the substrate's link end layers
#ifdef USE_BIASES
genes.push_back(GeneticNodeGene("Bias", "NetworkSensor", 0, false)); // bias for the CPPN
#endif // USE_BIASES
#ifdef USE_DELTAS
genes.push_back(GeneticNodeGene("DeltaX", "NetworkSensor", 0, false)); // offset between the two nodes on the X axis
genes.push_back(GeneticNodeGene("DeltaY", "NetworkSensor", 0, false)); // offset between the two nodes on the Y axis
genes.push_back(GeneticNodeGene("DeltaZ", "NetworkSensor", 0, false)); // offset between the two nodes on the Z axis
#endif // USE_DELTAS
#ifdef MODULAR_HNEAT
screen << "Laying out a heterogeneous controller CPPN" << endl;
genes.push_back(GeneticNodeGene("T1", "NetworkSensor", 0, false)); // position in the body
genes.push_back(GeneticNodeGene("T2", "NetworkSensor", 0, false)); // offset between the two nodes on the Z axis
#ifdef USE_DELTAS
genes.push_back(GeneticNodeGene("DeltaT", "NetworkSensor", 0, false)); // offset between the two nodes on the Z axis
#endif // USE_DELTAS
#endif // MODULAR_HNEAT
#ifndef MODULAR_HNEAT
screen << "Laying out a homogeneous controller CPPN" << endl;
#endif
// Configuration of the CCPPN's Output layer
genes.push_back(GeneticNodeGene("Output", "NetworkOutputNode", 1, false, ACTIVATION_FUNCTION_SIGMOID)); // weight for link between layers A and B
#ifdef USE_BIASES
genes.push_back(GeneticNodeGene("Bias_out", "NetworkOutputNode", 1, false, ACTIVATION_FUNCTION_SIGMOID)); // bias for the second sandwich layer
#endif // USE_BIASES
// Create the initial population
for (int a = 0; a < populationSize; a++) {
shared_ptr<GeneticIndividual> individual(new GeneticIndividual(genes, true, 1.0));
for (int b = 0; b < 0; b++) {
individual->testMutate();
}
population->addIndividual(individual);
}
screen << "Finished creating population\n";
// store population and individual size
popSize = population->getIndividualCount();
// screen << "\n individual count: " << popSize << "\n";
return population;
}
