public void InitialisePopulation()
{
if (Configuration.POPULATION_FILE != String.Empty)
{
Console.Write("Loading Initial Population... ");
members = Serializer.DeserializePopulation(new StreamReader(Configuration.POPULATION_FILE));
Console.WriteLine("Done");
}
else
{
int POPULATION_SIZE = Configuration.POPULATION_SIZE;
Console.WriteLine("Generating Initial Population... (0/" + POPULATION_SIZE + ")");
members = new PopulationMember[POPULATION_SIZE];
for (int i = 0; i < members.Length; i++)
{
do
{
members [i] = new PopulationMember();
} while (members[i].calculateFitness() == 0);
//Console.SetCursorPosition (0, 0);
//Console.Write ("Generating Initial Population... (" + i + "/" + INITIAL_POPULATION_SIZE + ")");
}
//Console.SetCursorPosition (0, 0);
Console.WriteLine("Generating Initial Population... Completed ");
Console.Write("Saving Population... ");
Serializer.SerializePopulation(members, new StreamWriter("LASTPOP_" + POPULATION_SIZE.ToString() + ".TXT", false));
Serializer.SerializePopulation(members, new StreamWriter("LASTPOP.TXT", false));
Console.WriteLine("Done");
}
}
private List <PopulationMember> addCrossoverMembers(List <PopulationMember> newPop, int numberToAdd)
{
//Console.WriteLine ("Beginning Crossover");
// The fittest members have are more likely to be crossed (likelihood is proportional to their fitness)
List <int> probabilityArray = new List <int> ();
//Console.WriteLine ("Caluclating Probability Array...");
for (int x = 0; x < newPop.Count; x++)
{
for (int i = 0; i < newPop[x].lastFitness; i++)
{
probabilityArray.Add(x);
}
}
for (int i = 0; i < numberToAdd; i++)
{
PopulationMember[] parents = new PopulationMember[Configuration.CROSSOVER_PARENT_COUNT];
for (int x = 0; x < parents.Length; x++)
{
parents [x] = newPop[probabilityArray [generator.next(0, probabilityArray.Count)]];
}
//Console.WriteLine ("{4}/{5}: Crossing {0} (fitness {1}) and {2} (fitness {3})", first, newPop[first].lastFitness, second, newPop[second].lastFitness, i, numberToAdd);
// Mutate crossover members
PopulationMember newMember = crosser.crossover(parents);
newMember = mutator.mutate(newMember);
// With a certain probability, the crossover will be dismissed and a brand new population member introduced
if (generator.next(0, Configuration.NEW_DURING_MUTATION_INVERSE) == 0)
{
PopulationMember p = new PopulationMember();
while (p.calculateFitness() < 1)
{
p = new PopulationMember();
}
newPop.Add(p);
}
else
{
newPop.Add(newMember);
}
//newPop.Add(crosser.crossover (newPop[first], newPop[second]));
}
return(newPop);
}
public PopulationMember[] select(PopulationMember[] current)
{
List <int> distList = new List <int> ();
int added = 0;
int toAdd = (int)Math.Round(current.Length * PROPORTION_TO_PICK, 0);
PopulationMember[] pNew = new PopulationMember[toAdd];
// Find the max fitness
int fitness = 0;
for (int x = 0; x < current.Length; x++)
{
if (current[x].lastFitness > fitness)
{
fitness = current[x].lastFitness;
added = 0;
}
if (added < pNew.Length && current [x].lastFitness == fitness)
{
pNew [added] = current [x];
added++;
}
}
for (int i = 0; i < current.Length; i++)
{
if (current [i].lastFitness != fitness)
{
for (int x = 0; x < current [i].lastFitness * current[i].lastFitness; x++)
{
distList.Add(i);
}
}
}
for (int i = added; i < pNew.Length; i++)
{
pNew [i] = current [distList[_generator.next(0, distList.Count)]];
}
return(pNew);
}
public PopulationMember[] select(PopulationMember[] current)
{
//Console.WriteLine("Selecting fittest population members...");
Array.Sort(current);
int min = current[current.Length - 1].lastFitness;
int knownMin = 1;
for (int i = current.Length - 2; i >= 0; i--)
{
if (current[i].lastFitness != min)
{
break;
}
else
{
knownMin++;
}
}
int required = (int)Math.Round(PROPORTION_TO_PICK * current.Length, 0);
int usable = current.Length - knownMin;
int toAddAtRandom = required - usable;
//Console.WriteLine ("Required: {0}, Usable: {1}, To Randomly Select: {2}", required, usable, toAddAtRandom);
PopulationMember[] newPop = new PopulationMember[required];
// Add the top n that aren't the lowest fitness in the group
for (int i = 0; i < usable && i < required; i++)
{
newPop[i] = current[i];
}
//Console.WriteLine ("Added usable members");
// Randomly choose the remaining from the lowest fitness population members
for (int i = usable; i < usable + toAddAtRandom; i++)
{
int n = _generator.next(usable, current.Length);
newPop[i] = current[n];
}
//Console.WriteLine ("Added random members");
return(newPop);
}
public PopulationMember crossover(PopulationMember[] parent)
{
PopulationMember first = parent [0];
PopulationMember second = parent [1];
int shortest = first.parameters.Length > second.parameters.Length ? second.parameters.Length : first.parameters.Length;
int crossoverPoint = _generator.next(4, shortest);
while (crossoverPoint % 4 != 0)
{
crossoverPoint--;
}
List <int> firstList = new List <int> ();
List <int> secondList = new List <int> ();
for (int i = 0; i < crossoverPoint; i++)
{
firstList.Add(first.parameters [i]);
secondList.Add(second.parameters [i]);
}
for (int i = crossoverPoint; i < second.parameters.Length; i++)
{
firstList.Add(second.parameters [i]);
}
for (int i = crossoverPoint; i < first.parameters.Length; i++)
{
secondList.Add(first.parameters [i]);
}
// Choose at random which to go with
PopulationMember p = new PopulationMember();
if (_generator.next(0, 2) == 0)
{
p.parameters = firstList.ToArray();
}
else
{
p.parameters = secondList.ToArray();
}
return(p);
}
public PopulationMember[] select(PopulationMember[] current)
{
List <int> distList = new List <int> ();
for (int i = 0; i < current.Length; i++)
{
for (int x = 0; x < current [i].lastFitness * current[i].lastFitness; x++)
{
distList.Add(i);
}
}
int toAdd = (int)Math.Round(current.Length * PROPORTION_TO_PICK, 0);
PopulationMember[] pNew = new PopulationMember[toAdd];
for (int i = 0; i < pNew.Length; i++)
{
pNew [i] = current [distList[_generator.next(0, distList.Count)]];
}
return(pNew);
}
public PopulationMember mutate(PopulationMember member)
{
PopulationMember newMember = new PopulationMember();
newMember.parameters = member.parameters;
for (int i = 0; i < member.parameters.Length; i += 4)
{
if (_generator.next(0, MUTATION_PROBABILITY_INVERSE) == 0)
{
switch (_generator.next(0, 8))
{
case 0:
//right
newMember.parameters [i]++;
newMember.parameters [i + 2]++;
break;
case 1:
//down
newMember.parameters [i + 1]--;
newMember.parameters [i + 3]--;
break;
case 2:
//left
newMember.parameters [i]--;
newMember.parameters [i + 2]--;
break;
case 3:
//up
newMember.parameters [i + 1]++;
newMember.parameters [i + 3]++;
break;
case 4:
//up-right
newMember.parameters [i]++;
newMember.parameters [i + 1]++;
newMember.parameters [i + 2]++;
newMember.parameters [i + 3]++;
break;
case 5:
//down-right
newMember.parameters [i]++;
newMember.parameters [i + 1]--;
newMember.parameters [i + 2]++;
newMember.parameters [i + 3]--;
break;
case 6:
//down-left
newMember.parameters [i]--;
newMember.parameters [i + 1]--;
newMember.parameters [i + 2]--;
newMember.parameters [i + 3]--;
break;
case 7:
//up-left
newMember.parameters [i]--;
newMember.parameters [i + 1]++;
member.parameters [i + 2]--;
member.parameters [i + 3]++;
break;
}
}
}
return(newMember);
}
public PopulationMember mutate(PopulationMember member)
{
PopulationMember newMember = new PopulationMember();
newMember.parameters = member.parameters;
int shiftAmount = _generator.next(0, 10) - 5; // Move up to 5 in either direction
for (int i = 0; i < member.parameters.Length; i += 4)
{
if (_generator.next(0, MUTATION_PROBABILITY_INVERSE) == 0)
{
switch (_generator.next(0, 8))
{
case 0:
//right
newMember.parameters [i] += shiftAmount;
newMember.parameters [i + 2] += shiftAmount;
break;
case 1:
//down
newMember.parameters [i + 1] -= shiftAmount;
newMember.parameters [i + 3] -= shiftAmount;
break;
case 2:
//left
newMember.parameters [i] -= shiftAmount;
newMember.parameters [i + 2] -= shiftAmount;
break;
case 3:
//up
newMember.parameters [i + 1] += shiftAmount;
newMember.parameters [i + 3] += shiftAmount;
break;
case 4:
//up-right
newMember.parameters [i] += shiftAmount;
newMember.parameters [i + 1] += shiftAmount;
newMember.parameters [i + 2] += shiftAmount;
newMember.parameters [i + 3] += shiftAmount;
break;
case 5:
//down-right
newMember.parameters [i]++;
newMember.parameters [i + 1] -= shiftAmount;
newMember.parameters [i + 2] += shiftAmount;
newMember.parameters [i + 3] -= shiftAmount;
break;
case 6:
//down-left
newMember.parameters [i] -= shiftAmount;
newMember.parameters [i + 1] -= shiftAmount;
newMember.parameters [i + 2] -= shiftAmount;
newMember.parameters [i + 3] -= shiftAmount;
break;
case 7:
//up-left
newMember.parameters [i] -= shiftAmount;
newMember.parameters [i + 1] += shiftAmount;
newMember.parameters [i + 2] -= shiftAmount;
newMember.parameters [i + 3] += shiftAmount;
break;
}
Direction newDir = (Direction)(_generator.next(0, 8));
Direction currentDir = determineDirection(newMember.parameters, i);
int[] parameters = newMember.parameters;
changeDirection(ref parameters, i, currentDir, newDir);
newMember.parameters = parameters;
}
}
return(newMember);
}
public PopulationMember mutate(PopulationMember member)
{
PopulationMember newMember = new PopulationMember();
newMember.parameters = member.parameters;
int shiftAmount = _generator.next(1, 11) - 6; // Move up to 5 in either direction
for (int i = 0; i < member.parameters.Length; i += 4)
{
if (_generator.next(0, MUTATION_PROBABILITY_INVERSE) == 0)
{
switch (_generator.next(0, 8))
{
case 0:
//right
newMember.parameters [i] += shiftAmount;
newMember.parameters [i + 2] += shiftAmount;
break;
case 1:
//down
newMember.parameters [i + 1] -= shiftAmount;
newMember.parameters [i + 3] -= shiftAmount;
break;
case 2:
//left
newMember.parameters [i] -= shiftAmount;
newMember.parameters [i + 2] -= shiftAmount;
break;
case 3:
//up
newMember.parameters [i + 1] += shiftAmount;
newMember.parameters [i + 3] += shiftAmount;
break;
case 4:
//up-right
newMember.parameters [i] += shiftAmount;
newMember.parameters [i + 1] += shiftAmount;
newMember.parameters [i + 2] += shiftAmount;
newMember.parameters [i + 3] += shiftAmount;
break;
case 5:
//down-right
newMember.parameters [i]++;
newMember.parameters [i + 1] -= shiftAmount;
newMember.parameters [i + 2] += shiftAmount;
newMember.parameters [i + 3] -= shiftAmount;
break;
case 6:
//down-left
newMember.parameters [i] -= shiftAmount;
newMember.parameters [i + 1] -= shiftAmount;
newMember.parameters [i + 2] -= shiftAmount;
newMember.parameters [i + 3] -= shiftAmount;
break;
case 7:
//up-left
newMember.parameters [i] -= shiftAmount;
newMember.parameters [i + 1] += shiftAmount;
newMember.parameters [i + 2] -= shiftAmount;
newMember.parameters [i + 3] += shiftAmount;
break;
}
}
}
return(newMember);
}
