void Evolver::doStep()
{
judge->parent = this;
if (genIdx == 0)
{
for (int i = 0; i < genSize; i++)
{
NeuralNet* n = new NeuralNet(1, 0, 1);
for (int i = 0; i < 10; i++)
{
n->mutate();
}
generation.push_back( n );
}
}
genIdx++;
setlocale(LC_ALL, "C");
generation = judge->rate(generation);
while(generation.size() < genSize)
{
NeuralNet* n = new NeuralNet(1, 0, 1);
*n = *generation[rand() % generation.size()];
for (int i = 0; i < 20; i++)
{
n->mutate();
}
generation.push_back(n);
}
}
void NeuroEvo::generate_new_members() {
// Mutate existing members to generate more
list<NeuralNet*>::iterator popMember = population.begin();
for (int i = 0; i < params->popSize; i++) { // add k new members
// commented out so that you take parent's evaluation
// (*popMember)->evaluation = 0.0;
// dereference pointer AND iterator
NeuralNet* m = new NeuralNet(**popMember);
m->mutate();
population.push_back(m);
++popMember;
}
}
