Encog.Neural.NEAT.Training.NEATTraining.Crossover C# (CSharp) Method

        public new NEATGenome Crossover(NEATGenome mom, NEATGenome dad)
        {
            NEATParent best;

            // first determine who is more fit, the mother or the father?
            if (mom.Score == dad.Score)
            {
                if (mom.NumGenes == dad.NumGenes)
                {
                    if (ThreadSafeRandom.NextDouble() > 0)
                    {
                        best = NEATParent.Mom;
                    }
                    else
                    {
                        best = NEATParent.Dad;
                    }
                }

                else
                {
                    if (mom.NumGenes < dad.NumGenes)
                    {
                        best = NEATParent.Mom;
                    }
                    else
                    {
                        best = NEATParent.Dad;
                    }
                }
            }
            else
            {
                if (Comparator.IsBetterThan(mom.Score, dad.Score))
                {
                    best = NEATParent.Mom;
                }

                else
                {
                    best = NEATParent.Dad;
                }
            }

            var babyNeurons = new Chromosome();
            var babyGenes = new Chromosome();

            var vecNeurons = new List<long>();

            int curMom = 0;
            int curDad = 0;

            NEATLinkGene momGene;
            NEATLinkGene dadGene;

            NEATLinkGene selectedGene = null;

            while ((curMom < mom.NumGenes) || (curDad < dad.NumGenes))
            {
                if (curMom < mom.NumGenes)
                {
                    momGene = (NEATLinkGene) mom.Links.Get(curMom);
                }
                else
                {
                    momGene = null;
                }

                if (curDad < dad.NumGenes)
                {
                    dadGene = (NEATLinkGene) dad.Links.Get(curDad);
                }
                else
                {
                    dadGene = null;
                }

                if ((momGene == null) && (dadGene != null))
                {
                    if (best == NEATParent.Dad)
                    {
                        selectedGene = dadGene;
                    }
                    curDad++;
                }
                else if ((dadGene == null) && (momGene != null))
                {
                    if (best == NEATParent.Mom)
                    {
                        selectedGene = momGene;
                    }
                    curMom++;
                }
                else if (momGene.InnovationId < dadGene.InnovationId)
                {
                    if (best == NEATParent.Mom)
                    {
                        selectedGene = momGene;
                    }
                    curMom++;
                }
                else if (dadGene.InnovationId < momGene.InnovationId)
                {
                    if (best == NEATParent.Dad)
                    {
                        selectedGene = dadGene;
                    }
                    curDad++;
                }
                else if (dadGene.InnovationId == momGene.InnovationId)
                {
                    if (ThreadSafeRandom.NextDouble() < 0.5f)
                    {
                        selectedGene = momGene;
                    }

                    else
                    {
                        selectedGene = dadGene;
                    }
                    curMom++;
                    curDad++;
                }

                if (babyGenes.Size() == 0)
                {
                    babyGenes.Add(selectedGene);
                }

                else
                {
                    if (((NEATLinkGene) babyGenes.Get(babyGenes.Size() - 1))
                            .InnovationId != selectedGene.InnovationId)
                    {
                        babyGenes.Add(selectedGene);
                    }
                }

                // Check if we already have the nodes referred to in SelectedGene.
                // If not, they need to be added.
                AddNeuronID(selectedGene.FromNeuronID, vecNeurons);
                AddNeuronID(selectedGene.ToNeuronID, vecNeurons);
            } // end while

            // now create the required nodes. First sort them into order
            vecNeurons.Sort();

            for (int i = 0; i < vecNeurons.Count; i++)
            {
                babyNeurons.Add(Innovations.CreateNeuronFromID(
                    vecNeurons[i]));
            }

            // finally, create the genome
            var babyGenome = new NEATGenome(Population
                                                .AssignGenomeID(), babyNeurons, babyGenes, mom.InputCount,
                                            mom.OutputCount);
            babyGenome.GA = this;
            babyGenome.Population = Population;

            return babyGenome;
        }