public void Play2048PatternTest2()
{
var selection = new EliteSelection();
var crossover = new TwoPointCrossover();
var mutation = new PartialShuffleMutation();
var fitness = new ClosestToMillion();
var bestChromosomeTodate = new Play2048Chromosome(20, new List <string>()
{
"up", "down", "left", "right"
});
//bestChromosomeTodate.Pattern = "";
var population = new Population(4, 5, bestChromosomeTodate);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.Termination = new GenerationNumberTermination(1);
Console.WriteLine("GA running...");
ga.GenerationRan += Ga_GenerationRan;
ga.Population.BestChromosomeChanged += Population_BestChromosomeChanged;
ga.Init();
//queue up all the patterns...
Console.WriteLine((bestChromosome as Play2048Chromosome).Pattern);
Console.WriteLine("Best solution found has {0} fitness was born in generation {1}", ga.BestChromosome.Fitness, bestGen);
}
public void Play2048PatternTest()
{
var selection = new EliteSelection();
var crossover = new TwoPointCrossover();
var mutation = new PartialShuffleMutation();
var fitness = new ClosestToMillion();
var chromosome = new Play2048Chromosome(20, new List <string>()
{
"up", "down", "left", "right"
});
var population = new Population(22, 42, chromosome);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.Termination = new GenerationNumberTermination(10);
Console.WriteLine("GA running...");
ga.GenerationRan += Ga_GenerationRan;
ga.Population.BestChromosomeChanged += Population_BestChromosomeChanged;
Task.Run(async() => { await Start(ga); }).Wait();
GA.GetSingleton().NextPattern = string.Empty;
Console.WriteLine((bestChromosome as Play2048Chromosome).Pattern);
Console.WriteLine("Best solution found has {0} fitness was born in generation {1}", ga.BestChromosome.Fitness, bestGen);
}
public void Play2048PatternTest()
{
var selection = new EliteSelection();
var crossover = new CutAndSpliceCrossover();
var mutation = new PartialShuffleMutation();
var fitness = new ClosestToMillion();
var chromosome = new Play2048Chromosome(20, new List <string>()
{
"up", "down", "left", "right"
});
var population = new CustomPopulation(2, 4, chromosome);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.Termination = new GenerationNumberTermination(10);
Console.WriteLine("GA running...");
ga.GenerationRan += Ga_GenerationRan;
Console.WriteLine("Best solution found has {0} fitness was born in generation {1}", ga.BestChromosome.Fitness, bestGen);
}
