Chromosome Breed(Chromosome a, Chromosome b)
{
bool mutateBet = Program.RNG.Next(500) == 0;
bool mutateScalar = Program.RNG.Next(500) == 0;
Chromosome child = new Chromosome(m_countMethods[Program.RNG.Next(m_countMethods.Length)],
Program.RNG.Next(2) == 0 ? a.CountScalar : b.CountScalar,
Program.RNG.Next(2) == 0 ? a.BetSize : b.BetSize);
child.Fitness = TestFitness(child);
return child;
}
List<Chromosome> GeneratePopulation(int count)
{
List<Chromosome> ret = new List<Chromosome>();
for (int i = 0; i < count; i++)
{
Chromosome chromosome = new Chromosome(m_countMethods[Program.RNG.Next(m_countMethods.Length)],
2, /* Program.RNG.Next(1, 21), /* Count Scalar */
5+i /* Bet size */
);
chromosome.Fitness = TestFitness(chromosome);
Console.WriteLine(i);
ret.Add(chromosome);
}
return ret;
}
double TestFitness(Chromosome chromosome)
{
DateTime startTime = DateTime.Now;
BlackjackGame game = new BlackjackGame(true, 6, chromosome.CountMethod, 0);
game.AddPlayer(new BasicStrategyAIEntity(chromosome.CountScalar, BANKROLL, chromosome.BetSize, 9999));
BasicStrategyAIEntity entity = game.RunGame(10000, BANKROLL * 100);
TimeSpan timeTaken = DateTime.Now - startTime;
double fitness = (double)entity.Balance;// *Math.Max(10000 - (float)timeTaken.TotalMilliseconds, 0);
chromosome.TimeAchieved = timeTaken.TotalMilliseconds;
chromosome.BalanceAchieved = entity.Balance;
if (fitness > m_highestSeenFitness)
{
m_highestSeenFitness = fitness;
m_fittestEntityResult = entity;
m_fittestChromosome = chromosome;
}
return fitness;
}
Chromosome GetFittest(Chromosome a, Chromosome b)
{
double aFitness = TestFitness(a);
double bFitness = TestFitness(b);
return aFitness > bFitness ? a : b;
}