public string Debug(SuperLightGA ga, float[] genome)
{
int start = Start;
string output = "";
for (int i = 0; i < MainClass.NumberOfSteps; i++)
{
float g1 = ga.ReadGene(genome, i, 0);
float g2 = ga.ReadGene(genome, i, 1);
int factor = (int)Math.Round(g1 * MaxJumpDistance);
if (g2 < 0.5f) // Subtract
{
output += string.Format("- {0} ", factor);
}
else // Add
{
output += string.Format("+ {0} ", factor);
}
start = Perform(
start,
ga.ReadGene(genome, i, 0),
ga.ReadGene(genome, i, 1)
);
if (start == Target)
{
break;
}
}
return(output + string.Format("= {0} ", start));
}
public static void Main(string[] args)
{
var jumpyFrog = new JumpFinder(1234);
Console.WriteLine("Target: {0}", jumpyFrog.Target);
Console.WriteLine("Start: {0}", jumpyFrog.Start);
var ga = new SuperLightGA();
// Population of 50. Keep Top-2 from each generation
ga.Initialize(50, 2, JumpFinder.MaxSteps, 2);
int generations = ga.Run(jumpyFrog, false);
Console.WriteLine("Generations: {0}", generations);
for (int i = 0; i < ga.SurvivalCount; i++)
{
Console.WriteLine(" {0}", jumpyFrog.Debug(ga, ga.BestGenomes[i]));
Console.WriteLine(" Score: {0}", ga.BestGenomeFitnesses[i]);
}
Console.ReadKey();
}
public float Evaluate(SuperLightGA ga, float[] genome)
{
int start = Start;
int numberOfSteps;
int score = 0;
for (numberOfSteps = 0; numberOfSteps < MainClass.NumberOfSteps; numberOfSteps++)
{
start = Perform(
start,
ga.ReadGene(genome, numberOfSteps, 0),
ga.ReadGene(genome, numberOfSteps, 1)
);
if (start == Target)
{
break;
}
// Evaluate based on # of jumps and distance from goal
score += (numberOfSteps + 1) * Math.Max(0, Math.Abs(Target - start));
}
return(score);
}