void* backgroundEvaluate(void* backgroundEvaluatorData )
{
assert(backgroundEvaluatorData!=NULL);
GAGenome* individual = ((BackgroundEvaluator*)backgroundEvaluatorData)->individual();
assert(individual);
individual->evaluate( );
((BackgroundEvaluator*)backgroundEvaluatorData)->finished(true);
return (backgroundEvaluatorData);
}
GAPopulation::GAPopulation(const GAGenome & c, unsigned int popsize) {
csz = N = GA_POP_CHUNKSIZE;
n = (popsize < 1 ? 1 : popsize);
while(N < n) N += csz;
rind = new GAGenome * [N];
sind = new GAGenome * [N];
for(unsigned int i=0; i<n; i++)
rind[i] = c.clone(GAGenome::ATTRIBUTES);
memcpy(sind, rind, N * sizeof(GAGenome*));
// indDiv = new float[N*N];
indDiv = 0;
neval = 0;
rawSum = rawAve = rawDev = rawVar = rawMax = rawMin = 0.0;
fitSum = fitAve = fitDev = fitVar = fitMax = fitMin = 0.0;
popDiv = -1.0;
rsorted = ssorted = evaluated = gaFalse;
scaled = statted = divved = selectready = gaFalse;
sortorder = HIGH_IS_BEST;
init = DefaultInitializer;
eval = DefaultEvaluator;
slct = new DEFAULT_SELECTOR;
slct->assign(*this);
sclscm = new DEFAULT_SCALING;
evaldata = nullptr;
ga = nullptr;
}
// Receive the bits from the specified task. Stuff the genome with the data.
// Returns a negative number if there was a transmission failure.
int
UnpackIndividual(GAGenome& g) {
GA1DBinaryStringGenome& genome = (GA1DBinaryStringGenome&)g;
int length = 0;
float score = 0.0;
static int nbits = 0;
static int* bits = 0;
int status = 0;
status = pvm_upkint(&length, 1, 1);
if(nbits < length){
nbits = length;
delete [] bits;
bits = new int [nbits];
}
status = pvm_upkint(bits, length, 1);
genome.length(length); // resize the genome
genome = bits; // stuff it with the bits
status = pvm_upkfloat(&score, 1, 1); // get the score from process
g.score(score); // set the score on the genome
return status;
}
// Send the bits of the genome to the task that requested them. First we send
// the number of bits, then we send the bits themselves. Note that we can
// handle genomes of varying lengths with this setup. We also pack the score
// and stuff that in as well (so that they don't have to do an eval at the
// other end). If we did this as a member function we could save the hassle
// of an extra copy of the bits...
// Returns negative number (error code) if failure.
int
PackIndividual(GAGenome& g) {
GA1DBinaryStringGenome& genome = (GA1DBinaryStringGenome&)g;
static int* bits = 0;
static int nbits = 0;
int status = 0;;
if(nbits < genome.length()){
nbits = genome.length();
delete [] bits;
bits = new int [nbits];
}
int length = genome.length();
for(int i=0; i<length; i++)
bits[i] = genome.gene(i);
status = pvm_pkint(&length, 1, 1);
status = pvm_pkint(bits, length, 1);
float score = g.score();
status = pvm_pkfloat(&score, 1, 1);
return status;
}
// When we create a GA, we stuff the parameters with the basics that will be
// needed by most genetic algorithms - num generations, p convergence, etc.
GAGeneticAlgorithm::GAGeneticAlgorithm(const GAGenome& g) : stats(), params() {
pop = new GAPopulation(g, gaDefPopSize);
pop->geneticAlgorithm(*this);
ud = nullptr;
cf = GAGeneticAlgorithm::DEFAULT_TERMINATOR;
d_seed = gaDefSeed;
params.add(gaNseed, gaSNseed, GAParameter::INT, &d_seed);
minmax = gaDefMiniMaxi;
params.add(gaNminimaxi, gaSNminimaxi, GAParameter::INT, &minmax);
ngen = gaDefNumGen;
params.add(gaNnGenerations, gaSNnGenerations, GAParameter::INT, &ngen);
nconv = gaDefNConv; stats.nConvergence(nconv);
params.add(gaNnConvergence, gaSNnConvergence, GAParameter::INT, &nconv);
pconv = gaDefPConv;
params.add(gaNpConvergence, gaSNpConvergence, GAParameter::FLOAT, &pconv);
pcross = gaDefPCross;
params.add(gaNpCrossover, gaSNpCrossover, GAParameter::FLOAT, &pcross);
pmut = gaDefPMut;
params.add(gaNpMutation, gaSNpMutation, GAParameter::FLOAT, &pmut);
int psize = pop->size();
params.add(gaNpopulationSize, gaSNpopulationSize, GAParameter::INT, &psize);
stats.scoreFrequency(gaDefScoreFrequency1);
params.add(gaNscoreFrequency, gaSNscoreFrequency,
GAParameter::INT, &gaDefScoreFrequency1);
stats.flushFrequency(gaDefFlushFrequency);
params.add(gaNflushFrequency, gaSNflushFrequency,
GAParameter::INT, &gaDefFlushFrequency);
stats.recordDiversity(gaDefDivFlag);
params.add(gaNrecordDiversity, gaSNrecordDiversity,
GAParameter::INT, &gaDefDivFlag);
stats.scoreFilename(gaDefScoreFilename);
params.add(gaNscoreFilename, gaSNscoreFilename,
GAParameter::STRING, gaDefScoreFilename);
stats.selectScores(gaDefSelectScores);
params.add(gaNselectScores, gaSNselectScores,
GAParameter::INT, &gaDefSelectScores);
stats.nBestGenomes(g, gaDefNumBestGenomes);
params.add(gaNnBestGenomes, gaSNnBestGenomes,
GAParameter::INT, &gaDefNumBestGenomes);
scross = g.sexual();
across = g.asexual();
}
// Receive the score and set it on the genome.
int
RecvGenomeScore(GAGenome& g) {
int status = 0;
float score = 0.0;
status = pvm_upkfloat(&score, 1, 1); // get the score from process
g.score(score); // set the score on the genome
return status;
}
// Send only the score of the genome to the specified task.
int
SendGenomeScore(GAGenome& g, int tid) {
int status = 0;
float score = g.score();
status = pvm_initsend(PvmDataDefault);
status = pvm_pkfloat(&score, 1, 1);
status = pvm_send(tid, MSG_GENOME_SCORE);
return status;
}
float
objective(GAGenome & c) {
GA2DBinaryStringGenome & genome = (GA2DBinaryStringGenome &)c;
short **pattern = (short **)c.userData();
float value=0.0;
for(int i=0; i<genome.width(); i++)
for(int j=0; j<genome.height(); j++)
value += (float)(genome.gene(i,j) == pattern[i][j]);
return(value);
}
/**
* The objective is the distance
*/
float Objective(GAGenome & g)
{
double x1, y1, z1;
double x2, y2, z2;
GeneticExperience *experience = (GeneticExperience *)g.userData();
if (experience == NULL) {
cout << "Score: unable to find the experience" << endl;
return 0;
}
cout << "Scoring... " << flush;
experience->updateSplines(g);
VREPClient &vrep = experience->getVrep();
//Main Loop
vrep.start();
x1 = vrep.readPositionTrackerX();
y1 = vrep.readPositionTrackerY();
z1 = vrep.readPositionTrackerZ();
for (double t=0; t<SIMULATION_TIME; t+=0.02) {
//Display state
//Do next step
vrep.nextStep();
//Compute motors move
primitive_step(vrep, experience->getSplines());
}
x2 = vrep.readPositionTrackerX();
y2 = vrep.readPositionTrackerY();
z2 = vrep.readPositionTrackerZ();
//End simulation
vrep.stop();
double score = sqrt(pow(x1-x2,2)+pow(y1-y2,2)+pow(z1-z2,2));
cout << score << endl;
return score;
}
float
GAGenome::NoComparator(const GAGenome& c, const GAGenome&)
{
GAErr(GA_LOC, c.className(), "comparator", gaErrOpUndef);
return -1.0;
}
int
GAGenome::NoMutator(GAGenome & c, float)
{
GAErr(GA_LOC, c.className(), "mutator", gaErrOpUndef);
return 0;
}
/// These are the default genome operators.
/// None does anything - they just post an error message to let you know that no
/// method has been defined. These are for the base class (which has no
/// function by itself).
void
GAGenome::NoInitializer(GAGenome & c)
{
GAErr(GA_LOC, c.className(), "initializer", gaErrOpUndef);
}
void
GADCrowdingGA::step() {
if(pop->size() == 0) return;
GAGenome *child = pop->individual(0).clone();
GAList<int> indpool;
for (int i=0; i<pop->size(); i++)
indpool.insert(i);
do {
int *ip;
indpool.warp(GARandomInt(0,indpool.size()-1)); // select mom
ip=indpool.remove();
GAGenome *mom = &pop->individual(*ip);
delete ip;
indpool.warp(GARandomInt(0,indpool.size()-1)); // select dad
ip=indpool.remove();
GAGenome *dad = &pop->individual(*ip);
delete ip;
stats.numsel += 2; // create child
stats.numcro += (*scross)(*mom, *dad, child, 0);
stats.nummut += child->mutate(pMutation());
stats.numeval += 1;
double d1 = child->compare(*mom); // replace closest parent
double d2 = child->compare(*dad);
if (d1 < d2) {
if (minmax == MINIMIZE) {
if (child->score() < mom->score()) {
mom->copy(*child);
stats.numrep += 1;
}
}
else {
if (child->score() > mom->score()) {
mom->copy(*child);
stats.numrep += 1;
}
}
}
else {
if (minmax == MINIMIZE) {
if (child->score() < dad->score()) {
dad->copy(*child);
stats.numrep += 1;
}
}
else {
if (child->score() > dad->score()) {
dad->copy(*child);
stats.numrep += 1;
}
}
}
} while (indpool.size()>1);
pop->evaluate(gaTrue);
stats.update(*pop);
delete child;
}
void PetriDish::GAPDEvaluator( GAPopulation & pop )
{
assert(pop.size() > 0);
// Since this is a static method, get this population's associated PetriDish
PetriDish* thisPetriDish = dynamic_cast<PetriDish*>(pop.geneticAlgorithm());
assert(thisPetriDish);
#ifdef USING_GASIMPLEGA
// A workaround for oldPop not copying our Evaluator to the next set of Genomes (as opposed to hacking GASimpleGA.C)
if ( thisPetriDish->_oldPopInitialized == false )
{
thisPetriDish->_oldPopInitialized = true;
thisPetriDish->oldPop->initialize();
}
#endif//USING_GASIMPLEGA
// Use all of the available cores (as reported by the processor) for threads
unsigned numberOfThreadsToUse;
#if USE_BOOST
numberOfThreadsToUse = boost::thread::hardware_concurrency();
#else//USE_BOOST
numberOfThreadsToUse = (unsigned)sysconf( _SC_NPROCESSORS_ONLN );
int errorCode;
#endif//USE_BOOST
// Allocate an array of pointers for the threads, as well as the associated background information
#if USE_BOOST
boost::thread** backgroundThreads = new boost::thread*[numberOfThreadsToUse];
#else//USE_BOOST
pthread_t* backgroundThreads = new pthread_t[numberOfThreadsToUse];
#endif//USE_BOOST
assert( backgroundThreads );
memset( backgroundThreads, 0, numberOfThreadsToUse * sizeof( void* ) );
BackgroundEvaluator** backgroundEvaluators = new BackgroundEvaluator*[numberOfThreadsToUse];
assert( backgroundEvaluators );
memset( backgroundEvaluators, 0, numberOfThreadsToUse * sizeof( BackgroundEvaluator* ) );
#if DEBUG
cout << "Evaluating new GAPopulation ( " << pop.size( ) << " )... ( using " << numberOfThreadsToUse << " threads )" << std::endl;
#endif//DEBUG
int completed = 0;
int indIndex = 0;
u_int32_t tIndex = 0U;
#if DEBUG
float highestScoreSoFar = 0.0f;
float total = 0.0f;
#endif//DEBUG
// Loop until every population member has been evaluated.
while ( completed < pop.size( ) && ( thisPetriDish->_interrupt == false ) )
{
// If we still have members to evaluate, and there's a free thread open
if ( ( indIndex < pop.size( ) ) && ( backgroundThreads[tIndex] == NULL ) )
{
// If we haven't allocated space for the evaluator thread information
if( backgroundEvaluators[tIndex] == NULL )
{
backgroundEvaluators[tIndex] = new BackgroundEvaluator( &pop.individual( indIndex ), indIndex );
assert( backgroundEvaluators[tIndex] != NULL );
}
else
{
assert(backgroundEvaluators[tIndex]->finished() == true);
backgroundEvaluators[tIndex]->newIndividual( &pop.individual( indIndex ), indIndex);
}
#if DEBUG
cout << "Starting individual #" << indIndex + 1 << " ( of " << pop.size( ) << " )" << std::endl;
#endif//DEBUG
// Kick off the thread
#if USE_BOOST
try
{
backgroundThreads[tIndex] = new boost::thread( boost::ref(*backgroundEvaluators[tIndex]) );
}
catch(const std::exception& e)
{
cerr << "boost::thread exception: " << e.what() << std::endl;
return;
}
#else//USE_BOOST
errorCode = pthread_create(&backgroundThreads[tIndex], NULL, backgroundEvaluate, backgroundEvaluators[tIndex]);
if (errorCode!=0)
{
cerr << "pthread_create: Error #"<< errorCode << " (" << strerror(errorCode) << ")" << std::endl;
return;
}
#endif//USE_BOOST
assert(backgroundThreads[tIndex]);
indIndex++;
}
// Our cyclic thread index checks for the completion of a running thread
tIndex = ( tIndex+1 ) % numberOfThreadsToUse;
// A (possibly still running) thread exists...
if ( backgroundThreads[tIndex] != NULL )
{
assert( backgroundEvaluators[tIndex] != NULL );
// Check to see if it is finished
if ( backgroundEvaluators[tIndex]->finished() )
{
// The thread has finished. Gather some stats (if DEBUGging) and free the thread up for the next individual
completed++;
#if DEBUG
GAGenome* genome = backgroundEvaluators[tIndex]->individual( );
float score = genome->score( );
total += score;
cout << "Received results from individual #" << backgroundEvaluators[tIndex]->index( ) << " ( " << completed << " of " << pop.size( ) <<
" finished ): Score: " << genome->score( ) << " (" << total / (float)completed << " is average so far)" << std::endl;
if ( score > highestScoreSoFar )
{
cout << "Found new high score so far: ( " << score << " > " << highestScoreSoFar <<" )" << std::endl;
highestScoreSoFar = score;
}
#endif//DEBUG
#if USE_BOOST
delete backgroundThreads[tIndex];
#else//USE_BOOST
errorCode = pthread_join(backgroundThreads[tIndex], NULL);
assert(errorCode==0);
#endif//USE_BOOST
backgroundThreads[tIndex] = NULL;
}
else
{
// If it hasn't finished yet, give up some main() thread processor time to the background evaluators
#if USE_BOOST
boost::thread::yield();
#else//USE_BOOST
pthread_yield();
#endif//USE_BOOST
}
}
}
if ( thisPetriDish->_interrupt == true )
{
cerr << "...evaluation interrupted!" << std::endl;
thisPetriDish->terminator(InterruptTerminator);
}
#if DEBUG
else
{
cout << "...finished evaluating this population." << std::endl;
}
#endif//DEBUG
for ( tIndex = 0; tIndex < numberOfThreadsToUse; tIndex++ )
{
if ( thisPetriDish->_interrupt == false )
{
// Double (sanity) check that all of the threads have actually been processed
assert( backgroundThreads[tIndex] == NULL );
if ( backgroundEvaluators[tIndex] != NULL ) // This can happen if all cores aren't used
{
assert( backgroundEvaluators[tIndex]->finished() == true );
}
}
else
{
// If the GA has been interrupted, try and clean up the background threads
if ( backgroundThreads[tIndex] != NULL )
{
#if USE_BOOST
backgroundThreads[tIndex]->interrupt();
delete backgroundThreads[tIndex];
#else//USE_BOOST
pthread_cancel(backgroundThreads[tIndex]);
errorCode = pthread_join(backgroundThreads[tIndex], NULL);
assert(errorCode==0);
#endif//USE_BOOST
backgroundThreads[tIndex] = NULL;
}
}
if ( backgroundEvaluators[tIndex] != NULL ) // This can happen if all cores aren't used
{
delete backgroundEvaluators[tIndex];
backgroundEvaluators[tIndex] = NULL;
}
}
// Free up the thread and background information arrays
if (backgroundThreads) {
delete[] backgroundThreads;
backgroundThreads = NULL;
}
if (backgroundEvaluators) {
delete[] backgroundEvaluators;
backgroundEvaluators = NULL;
}
}
