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));
}
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);
ga.Start();
var lastFitness = ((CheckersChromosome)ga.Population.BestChromosome).Fitness;
Assert.LessOrEqual(firstFitness, lastFitness);
}
public void Evaluate_ChromosomeForwardMove_Fitness05()
{
var target = new CheckersFitness(new CheckersBoard(8));
var chromosome = new CheckersChromosome(2, 8);
chromosome.Moves.Clear();
chromosome.Moves.Add(new CheckersMove(new CheckersPiece(CheckersPlayer.PlayerOne)
{
CurrentSquare = new CheckersSquare(1, 2)
}, new CheckersSquare(2, 3)));
Assert.AreEqual(0.5, target.Evaluate(chromosome));
}
private void Awake()
{
var population = new Population(m_populationSize, m_populationSize, new CheckersChromosome(m_movesAhead, m_boardSize));
Fitness = new CheckersFitness(new CheckersBoard(m_boardSize));
GA = new GeneticAlgorithm(
population,
Fitness,
new EliteSelection(),
new UniformCrossover(),
new UniformMutation());
GA.TaskExecutor = new SmartThreadPoolTaskExecutor();
GA.TaskExecutor.Timeout = System.TimeSpan.FromSeconds(1);
}
private void Awake()
{
Fitness = new CheckersFitness(new CheckersBoard(m_boardSize));
InitializeGA();
}
