{

delegate bool FitnessComparisonDelegate(Robot a, Robot b);

static class Program

{

const int startingPopulationSize = 500;

const int saveKillCount = 10; // Amount of fittest robots to save and least fit robots to kill at each generation

const int crossoverChance = 7; // 7 means 70% chance of crossover and 30% chance of mutation

const double fitnessThreshold = 1.0; // This is the fitness required for a successful solution

// If it is 1.0 then the solution is solved with a minimum path

// If it is ~9.0 then the goal is reached, but the path isn't as short as possible

#region Comparer

public class FitnessComparer : IComparer<Robot>

{

int IComparer<Robot>.Compare(Robot x, Robot y)

{

return ((new System.Collections.Comparer(System.Globalization.CultureInfo.CurrentCulture)).Compare(y.Fitness, x.Fitness));

}

}

#endregion

static void Main(string[] args)

{

Maze maze = new Maze();

Random rand = new Random(System.DateTime.Now.Millisecond);

List<Robot> robots = new List<Robot>();

int generation = 1;

//Create comma delimted output file and open stream to it

System.IO.StreamWriter streamWriter = new System.IO.StreamWriter(@"c:\Users\Pehr\Documents\robotDataFile.csv");

streamWriter.WriteLine("Initial Fitness:");

// Create initial population of robots

for (int i = 0; i < startingPopulationSize; i++)

{

robots.Add(new Robot(rand));

robots[i].ProcessRobot(maze);

System.Console.Write(robots[i].Fitness);

System.Console.Write(" ");

//Write intial data to output file

streamWriter.WriteLine(robots[i].Fitness);

}

// Sort our robots by fitness

FitnessComparer fitnessComparer = new FitnessComparer();

robots.Sort(fitnessComparer);

// While fitness[highest sorted] < 0.9 or maybe 1.0

while (robots[0].Fitness < fitnessThreshold)

{

// Save our fittest (first) 10 robots for the next generation and kill off the least fit 10 (last) robots

List<Robot> fittestRobots = new List<Robot>();

for (int i = 0; i < saveKillCount; i++)

{

robots.RemoveAt(robots.Count - 1);

fittestRobots.Add(new Robot(robots[i].GenoType, robots[i].Fitness));

}

// Randomly sort our robot list to create random pairs for crossover

robots.Sort(delegate(Robot x, Robot y) { return ((x.Fitness == y.Fitness) ? 0 : rand.Next(0, 1)); });

// Iterate through our list pairing robots and performing crossover or mutation

for (int i = 0; i < robots.Count; i++)

{

int crossoverMutationChoser = rand.Next(0, 9);

// 70% chance of crossover (and must be at least 2 robots left)

if (i < robots.Count - 1 && crossoverMutationChoser < crossoverChance)

{

Robot parentOne = robots[i];

Robot parentTwo = robots[i + 1];

Robot.Crossover(ref parentOne, ref parentTwo, rand);

// ProcessRobot will get a new fitness value

robots[i].ProcessRobot(maze);

robots[i+1].ProcessRobot(maze);

}

else

// 30% chance of mutation

{

robots[i].Mutate(rand);

// ProcessRobot will get a new fitness value

robots[i].ProcessRobot(maze);

}

}

// Re-add our fittest robots

for (int i = 0; i < saveKillCount; i++)

{

robots.Add(fittestRobots[i]);

}

generation++;

System.Console.Write("New generation: ");

// Put our robots in fitness sort order

robots.Sort(fitnessComparer);

streamWriter.WriteLine(String.Format("Fitness Generation[{0}]:", generation));

String phenoType = new String(robots[0].PhenoType);

streamWriter.WriteLine(String.Format("Fittest Phenotype: {0}", phenoType));

// Print out our current fitness data

for (int i = 0; i < robots.Count; i++)

{

System.Console.Write(robots[i].Fitness);

System.Console.Write(" ");

//Write current fitness data to output file

streamWriter.WriteLine(robots[i].Fitness);

}

}

System.Console.Write("Final fitness values: ");

streamWriter.WriteLine(String.Format("Final Fitness Generation[{0}]:", generation));

String pheno = new String(robots[0].PhenoType);

streamWriter.WriteLine(String.Format("Fittest Phenotype: {0}", pheno));

StreamWriter fitPhenoWriter = new StreamWriter(@"c:\Users\Pehr\Documents\robotSolution.txt");

fitPhenoWriter.Write(pheno);

fitPhenoWriter.Close();

for (int i = 0; i < robots.Count; i++)

{

System.Console.Write(robots[i].Fitness);

System.Console.Write(" ");

//Write current fitness data to output file

streamWriter.WriteLine(robots[i].Fitness);

}

streamWriter.Close();

// Wait for input so data can be viewed on console

System.Console.ReadKey();

}

}