MultiKultiControllerPtr MultiKultiInstance::getRandomMigrant(int nodeId){
vector<NewsItem*> * island = allItems[nodeId];
int i = Rand::randint(0,island->size());
ControllerPtr migrant = island->at(i)->getContent();
return boost::dynamic_pointer_cast<MultiKultiController>(migrant->Clone());
}
MultiKultiControllerPtr MultiKultiInstance::getBestMigrant(int nodeId){
vector<NewsItem*> * island = allItems[nodeId];
//int i = Rand::randint(0,island->size());
double bestFitness = island->at(0)->getContent()->GetOriginalFitness();
//cout<<"Island size"<<island->size()<<endl;
int best = 0;
//cout<<"0:"<<bestFitness<<endl;
for(unsigned int i =1;i<island->size();i++){
double actualFitness = island->at(i)->getContent()->GetOriginalFitness();
//cout<<i<<":"<<actualFitness<<endl;
if(actualFitness > bestFitness){
best = i;
bestFitness = actualFitness;
//cout<<"yay"<<endl;
}
}
//cout<<"Received "<<best<<"from node "<<nodeId<<endl;
ControllerPtr migrant = island->at(best)->getContent();
return boost::dynamic_pointer_cast<MultiKultiController>(migrant->Clone());
}
ControllerPtr PopulationControlArchitecture::getNextCandidate() {
currentTime++;
ControllerPtr candidate;
// if there is no full list of active solutions yet, generate a new candidate randomly
if (activeSolutions.size() < mu) {
candidate = this->createRandomGenome();
if (debug) {
cout << "Generated " << candidate->ToString() << endl;
}
}
// get news from the population, spreading the active solution
population->update(currentTime);
// if there is a full list of active solutions, mutate an existing solution or re-evaluate an active to create a new candidate
if (activeSolutions.size() == mu) {
// decide whether to re-evaluate or mutate a controller
if (Rand::randouble() < reEvaluationRate) { // re-evaluate
// pick one of the active solutions for re-evaluation
candidate = activeSolutions[Rand::randint(0, activeSolutions.size())];
if (debug) {
cout << "Selected re-evaluation of " << candidate->ToShortString() << endl;
}
} else { // mutate existing
// parent selection: random from the population
ControllerPtr parentA = selectParentByBinaryTournament(ControllerPtr());
if (debug) {
cout << "Selected first parent: " << parentA->ToShortString() << endl;
}
// crossover or clone; crossover only if there is a second active solution in the hivemind
if (population->getActiveCount() > 1 && Rand::randouble() < crossoverRate) {
if (debug) {
cout << "Selecting second parent, from a choice of " << population->getActiveCount() << endl;
}
// crossover
// select a second parent, excluding the first from the selection
vector<ControllerPtr> *parents = new vector<ControllerPtr>();
parents->push_back(parentA);
while (parents->size()<(unsigned) numberOfParents) {
if (debug) {
cout << parents->size() << endl;
}
ControllerPtr tmpC = selectParentsByBinaryTournament(parents);
parents->push_back(tmpC);
}
// create a candidate from crossover between the parents
candidate = parentA->crossOverWithMP(parents);
if (debug) {
cout << " Created " << candidate->ToShortString() << " from crossover between " << parents->at(0)->ToShortString();
for (uint i = 1; i < parents->size(); i++) cout << " and " << parents->at(i)->ToShortString();
cout << endl;
}
parents->clear();
delete parents;
} else {
// clone
candidate = parentA->Clone();
if (debug) {
cout << "Spawned " << candidate->ToShortString() << " from " << parentA->ToShortString() << endl;
}
}
// mutation
if (Rand::randouble() < mutationRate) {
//cout << "Before mutation: " << candidate->ToString() << endl;
candidate->mutate();
//cout << "After mutation: " << candidate->ToString() << endl;
if (debug) {
cout << "Mutated " << candidate->ToShortString() << endl;
}
}
}
}
return candidate;
}
void PopulationControlArchitecture::setCandidateFitness(ControllerPtr candidate, double scoredFitness) {
// running evaluation has completed. Decide if the candidate will become the active solution.
if (candidate->GetFitness() > -1) {
// this is a re-evaluation, average out the previous and the new score
if (debug) {
cout << "This was a re-evaluation, not adding a new candidate" << endl;
}
candidate->SetFitness((candidate->GetFitness() + scoredFitness) / 2);
if (debug || verbose) {
cout << "Finished re-evaluating " << candidate->ToShortString() << " - fitness: " << scoredFitness << ", avg: " << candidate->GetFitness() << endl;
}
} else {
candidate->SetFitness(scoredFitness);
// this is a first evaluation and will need to be considered for placement as an active solution
if (activeSolutions.size() < mu) {
// there is no full set of active solutions yet, just add this solution
activeSolutions.push_back(candidate);
// send out a news item about the new active solution
population->setNews(candidate->Clone(), activeSolutions.size() - 1, currentTime);
} else {
// there is a full list of active solutions, compete with the active solutions
int worstIndex = -1;
ControllerPtr worst = candidate;
// find the worst controller in the (unsorted) list
for (unsigned int i = 0; i < activeSolutions.size(); i++) {
if (worst->GetFitness() > activeSolutions[i]->GetFitness()) {
worst = activeSolutions[i];
worstIndex = i;
}
}
// if the candidate is better than the worst controller in the list, have it take that controller's place
if (scoredFitness > worst->GetFitness()) {
if (debug) {
cout << "This was first evaluation, candidate became active solution" << endl;
}
activeSolutions[worstIndex] = candidate;
// send out a news item about the new active solution
population->setNews(candidate->Clone(), worstIndex, currentTime);
} else {
if (debug) {
cout << "This was first evaluation, candidate failed" << endl;
}
// the candidate has lost the competition; have it deleted
// done automatically by smart pointer
}
}
// Don't print if candidate was deleted
if (candidate && (debug || verbose)) {
cout << "Finished evaluating " << candidate->ToShortString() << " - fitness: " << scoredFitness << endl;
}
}
if (!debug && !verbose) {
// there has been no output on the fitness yet, do that now
cout << scoredFitness << endl;
}
}
