442 lines
8.1 KiB
C++
442 lines
8.1 KiB
C++
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//
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#include "BitEvolver/Includes.h"
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#include "BitEvolver/Random.h"
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#include "BitEvolver/Population.h"
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#include "BitEvolver/Breeder.h"
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#include "BitEvolver/Chromosome.h"
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//
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#include <memory>
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#include <vector>
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#include <mutex>
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#include <iostream>
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#include <algorithm>
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#include <thread>
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//
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namespace BitEvolver
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{
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//
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using std::cout;
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using std::endl;
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//
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Population::Population()
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{
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//
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this->InitRandomGenerator();
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this->InitBreeder();
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//
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this->Reset();
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}
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//
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void Population::Reset()
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{
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//
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this->population_size = BIT_EVOLVER_POPULATION_DEFAULT_POPULATION_SIZE;
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this->SetMutationRate(BIT_EVOLVER_POPULATION_DEFAULT_MUTATE_RATE);
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this->evolution_number = 0;
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//
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this->RandomizePopulation(this->population_size);
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}
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//
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void Population::ClearPopulation()
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{
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//
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this->chromosomes.clear();
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this->evolution_number = 0;
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}
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//
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void Population::InitRandomPopulation(int _population_size, int _bit_length)
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{
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//
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this->population_size = _population_size;
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//
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this->RandomizePopulation(_bit_length);
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}
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//
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void Population::RandomizePopulation(int _bit_length)
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{
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//
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std::shared_ptr<Chromosome> chromosome;
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int i;
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//
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this->ClearPopulation();
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for ( i=0; i<this->population_size; i++ ) {
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//
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chromosome = std::shared_ptr<Chromosome>(
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new Chromosome( this->random, _bit_length )
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);
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this->chromosomes.push_back(chromosome);
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}
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}
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//
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void Population::PopulationChanged()
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{
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//
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this->population_needs_sorting = true;
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}
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//
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std::vector<std::shared_ptr<Chromosome>> Population::GetChromosomes()
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{
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return this->chromosomes;
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}
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//
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void Population::GetChromosomes(std::shared_ptr<std::vector<std::shared_ptr<Chromosome>>> _chromosomes)
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{
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//
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_chromosomes->clear();
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for ( std::shared_ptr<Chromosome> chromosome : this->chromosomes) {
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_chromosomes->push_back(chromosome);
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}
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}
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//
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std::shared_ptr<Chromosome> Population::GetChampion()
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{
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//
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this->EnsureSortedPopulation();
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//
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if ( this->chromosomes.size() > 0 ) {
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return this->chromosomes[0];
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}
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return nullptr;
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}
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//
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double Population::GetAverageFitness()
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{
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return this->GetAverageFitness(this->chromosomes);
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}
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//
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double Population::GetAverageFitness(std::vector<std::shared_ptr<Chromosome>> _chromosomes)
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{
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//
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double fitness_sum;
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double fitness_average;
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//
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fitness_sum = 0;
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for ( std::shared_ptr<Chromosome> chromosome : _chromosomes ) {
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fitness_sum += chromosome->GetFitness();
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}
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//
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fitness_average = 0;
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if ( _chromosomes.size() > 0 ) {
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fitness_average = fitness_sum / _chromosomes.size();
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}
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return fitness_average;
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}
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//
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void Population::SetCrossoverPoint(double p)
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{
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//
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this->crossover_point = p;
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}
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//
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double Population::GetCrossoverPoint()
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{
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//
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return this->crossover_point;
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}
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//
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void Population::SetCrossoverType(Enums::CrossoverType t)
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{
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//
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this->crossover_type = t;
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}
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//
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Enums::CrossoverType Population::GetCrossoverType()
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{
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//
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return this->crossover_type;
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}
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//
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void Population::SetMutationRate(double r)
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{
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//
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this->mutation_rate = r;
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}
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//
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double Population::GetMutationRate()
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{
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//
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return this->mutation_rate;
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}
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//
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void Population::Evolve()
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{
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//
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std::shared_ptr<std::vector< std::shared_ptr<Chromosome> > > population_new;
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//
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if ( this->chromosomes.size() == 0 ) {
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return;
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}
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//
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this->EnsureSortedPopulation();
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//
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population_new = std::shared_ptr<
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std::vector<
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std::shared_ptr<Chromosome>
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>
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>(
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new std::vector<std::shared_ptr<Chromosome>>()
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);
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// Start the new population off with our champion,
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// so the best score always carries over (elitism = 1 unit)
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#warning "Elitism is only 1 right now"
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population_new->push_back(this->chromosomes[0]);
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// Breed the new population
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this->BreedNewPopulation(population_new, (int)this->chromosomes.size());
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// Replace old population with the new
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this->chromosomes = *population_new;
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this->evolution_number++;
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//
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this->PopulationChanged();
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}
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//
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int Population::GetEvolutionNumber()
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{
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return this->evolution_number;
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}
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//
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void Population::PrintPopulation()
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{
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//
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this->EnsureSortedPopulation();
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this->PrintPopulation(this->chromosomes);
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}
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//
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void Population::PrintPopulation(std::vector<std::shared_ptr<Chromosome>> _chromosomes)
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{
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//
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for ( std::shared_ptr<Chromosome> chromosome : chromosomes ) {
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cout << chromosome->ToString() << endl;
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}
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cout << "Average Fitness --> " << this->GetAverageFitness(_chromosomes) << endl;
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}
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//
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void Population::InitRandomGenerator()
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{
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//
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this->random = std::shared_ptr<Random>(
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new Random()
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);
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}
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//
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void Population::InitBreeder()
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{
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//
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if ( !this->random ) {
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throw std::runtime_error("Population::InitBreeder() - Should come after InitRandomGenerator()");
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}
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//
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this->breeder = std::shared_ptr<Breeder>(
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new Breeder( this->random )
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);
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}
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//
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void Population::EnsureSortedPopulation()
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{
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//
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if ( !this->population_needs_sorting ) {
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return;
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}
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// Yay std::sort
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std::sort(
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this->chromosomes.begin(),
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this->chromosomes.end(),
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[]( std::shared_ptr<Chromosome>& left, std::shared_ptr<Chromosome>& right ) -> bool
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{
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//
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if ( left->GetFitness() > right->GetFitness() ) {
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return true;
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}
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return false;
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}
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);
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//
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this->population_needs_sorting = false;
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}
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//
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void Population::BreedNewPopulation(std::shared_ptr<std::vector<std::shared_ptr<Chromosome>>> population_new, int size)
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{
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//
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std::vector<std::shared_ptr<std::thread>> threads;
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std::shared_ptr<std::thread> thread;
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int
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thread_count,
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i
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;
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//
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thread_count = this->GetThreadCountSuggestion();
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//
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for ( i=0; i<thread_count; i++) {
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thread = std::shared_ptr<std::thread>(
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new std::thread(&Population::BreedNewPopulation_Thread, this, population_new, size)
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);
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threads.push_back(thread);
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}
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//
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for ( i=0; i<(int)threads.size(); i++) {
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threads[i]->join();
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}
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}
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//
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void Population::BreedNewPopulation_Thread(std::shared_ptr<std::vector<std::shared_ptr<Chromosome>>> population_new, int size)
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{
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//
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std::shared_ptr<Chromosome> kiddo;
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//
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while ( (int)population_new->size() < size )
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{
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//
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kiddo = this->BreedChild();
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// Mutexed
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this->breed_mutex.lock();
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if ( (int)population_new->size() < size ) {
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population_new->push_back(kiddo);
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}
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this->breed_mutex.unlock();
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}
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}
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//
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std::shared_ptr<Chromosome> Population::BreedChild()
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{
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//
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std::shared_ptr<Chromosome>
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mama, papa, kiddo
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;
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// Pick two parents
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mama = this->PickChromosomeForBreeding();
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papa = this->PickChromosomeForBreeding();
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//
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kiddo = this->breeder->Breed(
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mama, papa,
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this->crossover_type,
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this->crossover_point,
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this->mutation_rate
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);
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return kiddo;
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}
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/**
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(1) We want to pick the best chromosomes to repopulate
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(2) [not in lecture] We want to add a bit of randomness
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to the selection process, such that the worst chromosomes
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can still possibly be picked, and the best can still
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possibly be not-picked; Their fitness only increases
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the probability they're picked.
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*/
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std::shared_ptr<Chromosome> Population::PickChromosomeForBreeding()
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{
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//
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double normal;
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int chromosome_index;
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//
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this->EnsureSortedPopulation();
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/**
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Grab normal with 0 at the mean, and the standard deviation equal
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to 1/2 of the population size. Then make that an absolute value.
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This will make top/best chromosomes more likely to be picked,
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with the far/low end being much less likely
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*/
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#warning "Need to upgrade this to Roulette Wheel"
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// Repeat as needed, since the normal generator might actually
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// give us an out-of-bounds result sometimes
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while ( true )
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{
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//
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normal = this->random->GetNormal(0, 0.5);
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chromosome_index = abs( normal * this->chromosomes.size()
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);
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if ( chromosome_index >= 0 && chromosome_index < (int)this->chromosomes.size() ) {
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break;
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}
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}
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//
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return this->chromosomes[chromosome_index];
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}
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//
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int Population::GetThreadCountSuggestion()
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{
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//
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int thread_count;
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//
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thread_count = std::thread::hardware_concurrency();
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return thread_count;
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}
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};
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