/// <summary>
/// 执行遗传算法
/// </summary>
public void Start()
{
for (int i = 0; i < maxGenerationSize; i++)
{
//更新适应度
UpdateFitness();
//按照适应度排序
GenomeList.Sort();
////如果最优个体的适应性度量值=最差个体的适应性度量值
if (GenomeList.Count == 0 || GenomeList[GenomeList.Count - 1].Fitness == GenomeList[0].Fitness)
{
break;
}
//将第解赋值给最优个体
if (Math.Abs(GenomeList[GenomeList.Count - 1].Fitness) < Math.Abs(GenomeList[0].Fitness))
{
this.bestGenome = GenomeList[0];
}
else
{
this.bestGenome = GenomeList[GenomeList.Count - 1];
}
//选择复制
Selection();
//繁衍子代--交叉
Breed();
//变异
Mutation();
//将下一代种群重新赋值给种群容器
GenomeList = nextGenomeList;
}
}
/// <summary>
/// 更新群体适应度
/// </summary>
private void UpdateFitness()
{
//计算适应度
if (fitnessCalculator == null)
{
throw new Exception("没有初始化 FitnessFunction 委托");
}
foreach (Genome genome in genomeList)
{
fitnessCalculator(genome);
}
//按照适应度排序
GenomeList.Sort();
}
public void rankGenomes()
{
int size = population.Count;
//TODO: JUSTIN: This needs to be handled elsewhere. Call it when novelty is calculated in EvolutionAlgorithm.cs so that we can set the objective properly when the others are set.
//calculateGenomicNovelty();
/*if(doNovelty) {
* measure_novelty();
* }//*/
//reset rank information
for (int i = 0; i < size; i++)
{
if (ranks.Count < (i + 1))
{
ranks.Add(new RankInformation());
}
else
{
ranks[i].reset();
}
}
/*Console.WriteLine("Did it reset properly?");
* foreach (RankInformation r in ranks)
* {
* Console.WriteLine(r.domination_count + " " + r.rank + " " + r.ranked);
* }
* Console.WriteLine("Dunno, maybe you should check if that spam is all zeroes and falses.");//*///Yeah. It reset properly.
//calculate domination by testing each genome against every other genome
for (int i = 0; i < size; i++)
{
for (int j = 0; j < size; j++)
{
update_domination((NeatGenome.NeatGenome)population[i], (NeatGenome.NeatGenome)population[j], ranks[i], ranks[j]);
}
}
//successively peel off non-dominated fronts (e.g. those genomes no longer dominated by any in
//the remaining population)
List <int> front = new List <int>();
int ranked_count = 0;
int current_rank = 1;
while (ranked_count < size)
{
//search for non-dominated front
for (int i = 0; i < size; i++)
{
//continue if already ranked
if (ranks[i].ranked)
{
continue;
}
//if not dominated, add to front
if (ranks[i].domination_count == 0)
{
front.Add(i);
ranks[i].ranked = true;
ranks[i].rank = current_rank;
}
}
int front_size = front.Count;
//Console.WriteLine("Front " + current_rank + " size: " + front_size);
//now take all the non-dominated individuals, see who they dominated, and decrease
//those genomes' domination counts, because we are removing this front from consideration
//to find the next front of individuals non-dominated by the remaining individuals in
//the population
for (int i = 0; i < front_size; i++)
{
RankInformation r = ranks[front[i]];
foreach (RankInformation dominated in r.dominates)
{
dominated.domination_count--;
}
}
ranked_count += front_size;
front.Clear();
current_rank++;
}
//we save the last objective for potential use as genomic novelty objective
int last_obj = population[0].objectives.Length - 1;
//fitness = popsize-rank (better way might be maxranks+1-rank), but doesn't matter
//because speciation is not used and tournament selection is employed
for (int i = 0; i < size; i++)
{
//population[i].Fitness = (size+1)-ranks[i].rank;//+population[i].objectives[last_obj]/100000.0;
population[i].Fitness = (current_rank + 1) - ranks[i].rank;
}
/*foreach (RankInformation r in ranks)
* {
* Console.WriteLine("After ranking: " + r.domination_count + " " + r.rank + " " + r.ranked);
* }//*/
population.Sort();
/*foreach (IGenome aye in population)
* {
* Console.Write(aye.Fitness + " : [" + aye.RealFitness + "] : ");
* foreach (double d in aye.objectives) Console.Write(d + " ");
* Console.WriteLine();
* }//*/
generation++;
/*if(generation%50==0)
* this.printDistribution();//*///JUSTIN: Don't do this.. takes up too much space. Also doesn't currently work for multiple runs.
}
public void rankGenomes()
{
int size = population.Count;
calculateGenomicNovelty();
if (doNovelty)
{
measure_novelty();
}
//reset rank information
for (int i = 0; i < size; i++)
{
if (ranks.Count < i + 1)
{
ranks.Add(new RankInformation());
}
else
{
ranks[i].reset();
}
}
//calculate domination by testing each genome against every other genome
for (int i = 0; i < size; i++)
{
for (int j = 0; j < size; j++)
{
update_domination((NeatGenome.NeatGenome)population[i], (NeatGenome.NeatGenome)population[j], ranks[i], ranks[j]);
}
}
//successively peel off non-dominated fronts (e.g. those genomes no longer dominated by any in
//the remaining population)
List <int> front = new List <int>();
int ranked_count = 0;
int current_rank = 1;
while (ranked_count < size)
{
//search for non-dominated front
for (int i = 0; i < size; i++)
{
//continue if already ranked
if (ranks[i].ranked)
{
continue;
}
//if not dominated, add to front
if (ranks[i].domination_count == 0)
{
front.Add(i);
ranks[i].ranked = true;
ranks[i].rank = current_rank;
}
}
int front_size = front.Count;
Console.WriteLine("Front " + current_rank + " size: " + front_size);
//now take all the non-dominated individuals, see who they dominated, and decrease
//those genomes' domination counts, because we are removing this front from consideration
//to find the next front of individuals non-dominated by the remaining individuals in
//the population
for (int i = 0; i < front_size; i++)
{
RankInformation r = ranks[front[i]];
foreach (RankInformation dominated in r.dominates)
{
dominated.domination_count--;
}
}
ranked_count += front_size;
front.Clear();
current_rank++;
}
//we save the last objective for potential use as genomic novelty objective
int last_obj = population[0].objectives.Length - 1;
//fitness = popsize-rank (better way might be maxranks+1-rank), but doesn't matter
//because speciation is not used and tournament selection is employed
for (int i = 0; i < size; i++)
{
population[i].Fitness = (size + 1) - ranks[i].rank; //+population[i].objectives[last_obj]/100000.0;
}
population.Sort();
generation++;
if (generation % 250 == 0)
{
this.printDistribution();
}
}