Exemplo n.º 1
0
		//if genome x dominates y, increment y's dominated count, add y to x's dominated list
		public void update_domination(NeatGenome.NeatGenome x, NeatGenome.NeatGenome y,RankInformation r1,RankInformation r2)
		{
			if(dominates(x,y)) {
				r1.dominates.Add(r2);
				r2.domination_count++;
			}
		}
Exemplo n.º 2
0
 //if genome x dominates y, increment y's dominated count, add y to x's dominated list
 public void update_domination(NeatGenome.NeatGenome x, NeatGenome.NeatGenome y, RankInformation r1, RankInformation r2)
 {
     if (dominates(x, y))
     {
         r1.dominates.Add(r2);
         r2.domination_count++;
     }
 }
Exemplo n.º 3
0
        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.
        }
Exemplo n.º 4
0
        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();
            }
        }