public override void CopyGeneInfo(Genome dest) { MastermindGenome theGene = (MastermindGenome)dest; theGene.Length = Length; theGene.TheMin = TheMin; theGene.TheMax = TheMax; }
public MasterMindPopulation(int numberOfGenomes) { Genomes.Clear(); for (int i = 0; i < numberOfGenomes; i++) { MastermindGenome aGenome = new MastermindGenome(kLength, 1, 9); aGenome.SetCrossoverPoint(kCrossover); aGenome.CalculateFitness(); Genomes.Add(aGenome); } }
public override Genome Crossover(Genome g) { MastermindGenome aGene1 = new MastermindGenome(); MastermindGenome aGene2 = new MastermindGenome(); g.CopyGeneInfo(aGene1); g.CopyGeneInfo(aGene2); MastermindGenome CrossingGene = (MastermindGenome)g; for (int i = 0; i < CrossoverPoint; i++) { aGene1.TheArray.Add(CrossingGene.TheArray[i]); aGene2.TheArray.Add(TheArray[i]); } for (int j = CrossoverPoint; j < Length; j++) { aGene1.TheArray.Add(TheArray[j]); aGene2.TheArray.Add(CrossingGene.TheArray[j]); } // 50/50 chance of returning gene1 or gene2 MastermindGenome aGene = null; if (TheSeed.Next(2) == 1) { aGene = aGene1; } else { aGene = aGene2; } return(aGene); }
public void DoCrossover(ArrayList genes) { ArrayList GeneMoms = new ArrayList(); ArrayList GeneDads = new ArrayList(); for (int i = 0; i < genes.Count; i++) { // randomly pick the moms and dad's if (MastermindGenome.TheSeed.Next(100) % 2 > 0) { GeneMoms.Add(genes[i]); } else { GeneDads.Add(genes[i]); } } // now make them equal if (GeneMoms.Count > GeneDads.Count) { while (GeneMoms.Count > GeneDads.Count) { GeneDads.Add(GeneMoms[GeneMoms.Count - 1]); GeneMoms.RemoveAt(GeneMoms.Count - 1); } if (GeneDads.Count > GeneMoms.Count) { GeneDads.RemoveAt(GeneDads.Count - 1); // make sure they are equal } } else { while (GeneDads.Count > GeneMoms.Count) { GeneMoms.Add(GeneDads[GeneDads.Count - 1]); GeneDads.RemoveAt(GeneDads.Count - 1); } if (GeneMoms.Count > GeneDads.Count) { GeneMoms.RemoveAt(GeneMoms.Count - 1); // make sure they are equal } } // now cross them over and add them according to fitness for (int i = 0; i < GeneDads.Count; i++) { // pick best 2 from parent and children MastermindGenome babyGene1 = (MastermindGenome)((MastermindGenome)GeneDads[i]).Crossover((MastermindGenome)GeneMoms[i]); MastermindGenome babyGene2 = (MastermindGenome)((MastermindGenome)GeneMoms[i]).Crossover((MastermindGenome)GeneDads[i]); GenomeFamily.Clear(); GenomeFamily.Add(GeneDads[i]); GenomeFamily.Add(GeneMoms[i]); GenomeFamily.Add(babyGene1); GenomeFamily.Add(babyGene2); CalculateFitnessForAll(GenomeFamily); GenomeFamily.Sort(); if (Best2 == true) { // if Best2 is true, add top fitness genes GenomeResults.Add(GenomeFamily[0]); GenomeResults.Add(GenomeFamily[1]); } else { GenomeResults.Add(babyGene1); GenomeResults.Add(babyGene2); } } }