public void Evolve_ManyGenerations_Fast()
{
int movesAhead = 10;
int boardSize = 10;
var selection = new EliteSelection();
var crossover = new OrderedCrossover();
var mutation = new TworsMutation();
var chromosome = new CheckersChromosome(movesAhead, boardSize);
var fitness = new CheckersFitness(new CheckersBoard(boardSize));
var population = new Population(40, 40, chromosome);
var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.GenerationRan += delegate
{
if (ga.Population.GenerationsNumber % 100 == 0)
{
fitness.Update(ga.Population.BestChromosome as CheckersChromosome);
}
};
ga.Start();
var firstFitness = ((CheckersChromosome)ga.Population.BestChromosome).Fitness;
ga.Termination = new GenerationNumberTermination(2001);
TimeAssert.LessThan(100000, () =>
{
ga.Start();
});
var lastFitness = ((CheckersChromosome)ga.Population.BestChromosome).Fitness;
Assert.LessOrEqual(firstFitness, lastFitness);
}
public void Evaluate_ChromosomeForwardMoveAndCanCaptureAnotherOne_Fitness2()
{
var board = new CheckersBoard(8);
var target = new CheckersFitness(board);
var move = new CheckersMove(new CheckersPiece(CheckersPlayer.PlayerOne) { CurrentSquare = new CheckersSquare(3, 2) }, new CheckersSquare(4, 3));
Assert.IsTrue(board.MovePiece(move));
move = new CheckersMove(new CheckersPiece(CheckersPlayer.PlayerTwo) { CurrentSquare = new CheckersSquare(6, 5) }, new CheckersSquare(5, 4));
Assert.IsTrue(board.MovePiece(move));
var chromosome = new CheckersChromosome(2, 8);
chromosome.Moves.Clear();
chromosome.Moves.Add(new CheckersMove(new CheckersPiece(CheckersPlayer.PlayerOne) { CurrentSquare = new CheckersSquare(4, 3) }, new CheckersSquare(6, 5)));
target.Update(chromosome);
Assert.AreEqual(2, target.Evaluate(chromosome));
}
