void SweeperLiveScene::startGeneration()
{
// 显示当前时代;
int nGeneration = GeneticAlgorithm::instance()->getGeneration();
char szGeneration[32];
sprintf(szGeneration, "Generation: %d", nGeneration);
m_labelGeneration->setString(szGeneration);
// 计数归零;
m_generationCurrentTicks = 0;
// 适应值归零，重新设计基因;
for (int i=0; i<CONSTANTS.SweeperNumber; ++i)
{
auto sweeper = m_sweepers[i];
// 设置随机位置;
sweeper->setFixedPosition(this->randomFixedPosition());
// 适应值归零;
sweeper->resetFitness();
// 设置基因;
const auto &genes = GeneticAlgorithm::instance()->getGenome(i);
sweeper->setGenome(genes);
}
}
/******************************************************************************
Function evolutionStep - controls one evolution step, is called for each
generation, manages the deffirences between CGP and coevolution
Takes parameters:
@input - pointer to an array of all training vectors
@geneticP - pointer to a struct of all CGP params
@geneticArray - pointer to a vector of whole population
@functions - pointer to an array of available functions
@test - pointer to the test - in variant without coevolution is NULL
******************************************************************************/
void evolutionStep(TData* input, TCgpProperties* geneticP, vector<TIndividual>* geneticArray, TFuncAvailable* functions, TTest* test){
#ifdef COEVOLUTION
//copy test vector from shared memory
TCoevIndividual* testVect = NULL;
testVect = (TCoevIndividual*)malloc(sizeof(struct test));
pthread_mutex_lock(&test->test_sem);
testVect->value = new vector<int>(*test->test.value);
pthread_mutex_unlock(&test->test_sem);
#endif
getActiveNodes(geneticArray, geneticP);
for(int ind = 0; ind < geneticP->individCount; ind++){
resetFitness(&geneticArray->at(ind));
#ifdef COEVOLUTION
for(int i = 0; i < geneticP->testSize; i++){
getValue(&geneticArray->at(ind), geneticP, input->data[testVect->value->at(i)]);
getFitness(&geneticArray->at(ind), geneticP, input->data[testVect->value->at(i)]);
}//for all tests
#else
for(int i = 0; i < input->dataCount; i++){
getValue(&geneticArray->at(ind), geneticP, input->data[i]);
getFitness(&geneticArray->at(ind), geneticP, input->data[i]);
}//for all inputs
#endif
}//for all individuals
#ifdef COEVOLUTION
//tidy up the test vector
delete(testVect->value);
free(testVect);
#endif
getParents(geneticArray, geneticP);
createChildren(geneticArray, geneticP, functions);
}
