public Position calculateAlpha(List <Krill> herd, Krill krill, HerdParameters parameters)
{
Position localAlpha = calculateAlphaLocal(herd, krill, parameters);
Position targetAlpha = calculateAlphaTarget(parameters, krill);
return(localAlpha + targetAlpha);
}
public Position calculateBeta(Krill krill, Food food, HerdParameters parameters)
{
Position betaFood = calculateBetaFood(food,krill);
Position betaBest = calculateBetaBest(krill,parameters);
//Debug.Log("Food " + betaFood + " best " + betaBest);
return betaFood + betaBest;
}
public Position calculateAlpha(List<Krill> herd, Krill krill, HerdParameters parameters)
{
Position localAlpha = calculateAlphaLocal(herd, krill, parameters);
Position targetAlpha = calculateAlphaTarget(parameters,krill);
return localAlpha + targetAlpha;
}
public Position calculateBeta(Krill krill, Food food, HerdParameters parameters)
{
Position betaFood = calculateBetaFood(food, krill);
Position betaBest = calculateBetaBest(krill, parameters);
//Debug.Log("Food " + betaFood + " best " + betaBest);
return(betaFood + betaBest);
}
private Position calculateBetaBest(Krill krill, HerdParameters parameters)
{
Position bestRelatedPosition = tendencyCalculator.calculateRelatedPosition(krill.getBestPosition(),krill.getPosition());
float bestFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(),krill.getBestPositionFitness(),parameters);
//Debug.Log("best fitness " + bestFitness);
bestRelatedPosition = bestRelatedPosition * bestFitness;
return bestRelatedPosition;
}
private void mutateKrill(Krill krill, List<Krill> herd, HerdParameters parameters)
{
int range = herd.Count / 2;
Krill first = herd[Random.Range(0,range)];
int secondIndex = Random.Range(range,herd.Count);
Krill second = herd[secondIndex];
// krill.mutate(first,second,parameters.getBestFitnessKrill());
}
private void mutateKrill(Krill krill, List <Krill> herd, HerdParameters parameters)
{
int range = herd.Count / 2;
Krill first = herd[Random.Range(0, range)];
int secondIndex = Random.Range(range, herd.Count);
Krill second = herd[secondIndex];
// krill.mutate(first,second,parameters.getBestFitnessKrill());
}
static void ImplementInterfaces()
{
Jaguar jaguar = new Jaguar();
Console.WriteLine(jaguar.Sleep);
Krill krill = new Krill();
Console.WriteLine(krill.Swim);
}
private float calculateSenseDistance(List<Krill> herd, Krill krill)
{
float distance = 0.0f;
foreach(Krill other in herd){
distance += krill.getPosition().distanceFrom(other.getPosition());
}
return distance/(5.0f * herd.Count);
}
private Position calculateBetaBest(Krill krill, HerdParameters parameters)
{
Position bestRelatedPosition = tendencyCalculator.calculateRelatedPosition(krill.getBestPosition(), krill.getPosition());
float bestFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), krill.getBestPositionFitness(), parameters);
//Debug.Log("best fitness " + bestFitness);
bestRelatedPosition = bestRelatedPosition * bestFitness;
return(bestRelatedPosition);
}
private Position calculateAlphaTarget(HerdParameters parameters, Krill krill)
{
Position relatedPosition = tendencyCalculator.calculateRelatedPosition(parameters.getBestFitnessPosition(), krill.getPosition());
float relatedFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(),parameters.getBestFitnessValue(), parameters);
relatedPosition = relatedPosition * relatedFitness;
relatedPosition = relatedPosition * calculateCoefficient(parameters);
return relatedPosition;
}
private Position calculateAlphaTarget(HerdParameters parameters, Krill krill)
{
Position relatedPosition = tendencyCalculator.calculateRelatedPosition(parameters.getBestFitnessPosition(), krill.getPosition());
float relatedFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), parameters.getBestFitnessValue(), parameters);
relatedPosition = relatedPosition * relatedFitness;
relatedPosition = relatedPosition * calculateCoefficient(parameters);
return(relatedPosition);
}
private float calculateSenseDistance(List <Krill> herd, Krill krill)
{
float distance = 0.0f;
foreach (Krill other in herd)
{
distance += krill.getPosition().distanceFrom(other.getPosition());
}
return(distance / (5.0f * herd.Count));
}
public void updateBestWorstKrill(Krill krill)
{
if(krill.getFitnessValue() < bestFitnessValue){
bestKrill = krill;
bestFitnessValue = krill.getFitnessValue();
bestFitnessPosition = krill.getPosition().getClone();
}
if(krill.getFitnessValue() > worstFitnessValue){
worstFitnessValue = krill.getFitnessValue();
}
}
private Position calculateAlphaLocal(List<Krill> neighbours, Krill krill, HerdParameters parameters)
{
Position alphaLocal = new Position();
foreach (Krill neighbour in neighbours) {
Position relatedPosition = tendencyCalculator.calculateRelatedPosition(neighbour.getPosition(), krill.getPosition());
float relatedFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(),neighbour.getFitnessValue(), parameters);
relatedPosition = relatedPosition * relatedFitness;
alphaLocal = alphaLocal + relatedPosition;
}
return alphaLocal;
}
public void updateBestWorstKrill(Krill krill)
{
if (krill.getFitnessValue() < bestFitnessValue)
{
bestKrill = krill;
bestFitnessValue = krill.getFitnessValue();
bestFitnessPosition = krill.getPosition().getClone();
}
if (krill.getFitnessValue() > worstFitnessValue)
{
worstFitnessValue = krill.getFitnessValue();
}
}
private Position calculateAlphaLocal(List <Krill> neighbours, Krill krill, HerdParameters parameters)
{
Position alphaLocal = new Position();
foreach (Krill neighbour in neighbours)
{
Position relatedPosition = tendencyCalculator.calculateRelatedPosition(neighbour.getPosition(), krill.getPosition());
float relatedFitness = tendencyCalculator.calculateRelatedFitness(krill.getFitnessValue(), neighbour.getFitnessValue(), parameters);
relatedPosition = relatedPosition * relatedFitness;
alphaLocal = alphaLocal + relatedPosition;
}
return(alphaLocal);
}
public Krill simulate()
{
init();
while (algorithmParameters.nextIteration())
{
fitnessEvaluation();
motionCalculations();
updateKrillPositions();
}
Krill bestKrill = algorithmParameters.getBestFitnessKrill();
bestKrill.calculateSpeed();
return(bestKrill);
}
public List<Krill> determinateNeighbours(List<Krill> herd, Krill krill)
{
List<Krill> neighbours = new List<Krill>();
float senseDistance = calculateSenseDistance(herd,krill);
foreach(Krill other in herd){
if(!(krill==other)){
float distance = krill.getPosition().distanceFrom(other.getPosition());
if(distance <= senseDistance){
neighbours.Add(other);
}
}
}
return neighbours;
}
public List <Krill> determinateNeighbours(List <Krill> herd, Krill krill)
{
List <Krill> neighbours = new List <Krill>();
float senseDistance = calculateSenseDistance(herd, krill);
foreach (Krill other in herd)
{
if (!(krill == other))
{
float distance = krill.getPosition().distanceFrom(other.getPosition());
if (distance <= senseDistance)
{
neighbours.Add(other);
}
}
}
return(neighbours);
}
static void OverrideVirtualMethods()
{
// Override two virtual methods
// Create animal objects and instantiate concrete animals
Parrot parrot = new Parrot();
Console.WriteLine(parrot.Fly());
Toucan toucan = new Toucan();
Console.WriteLine(toucan.Fly());
Krill krill = new Krill();
Console.WriteLine(krill.BeEaten());
Langostino langostino = new Langostino();
Console.WriteLine(langostino.BeEaten());
}
public int getVerticalInput()
{
bestKrill = herd.simulate();
return(angleDirection(bestKrill.getPosition().toVector3()));
}
private Position calculateBetaFood(Food food, Krill krill )
{
return null;
}
public int getVerticalInput()
{
bestKrill = herd.simulate();
return angleDirection(bestKrill.getPosition().toVector3());
}
private Position calculateBetaFood(Food food, Krill krill)
{
return(null);
}
private void crossKrill(Krill toCross, List<Krill> herd)
{
int ind = Random.Range(0,herd.Count);
// toCross.crossover(herd[ind]);
}
public void TestSwim()
{
Krill krill = new Krill();
Assert.Equal("Crustaceans can swim.", krill.Swim);
}
private Position getAlphaPosition(List <Krill> herd, Krill krill, HerdParameters parameters)
{
Position alphaPosition = alphaCalculator.calculateAlpha(herd, krill, parameters);
return(alphaPosition * parameters.N_MAX);
}
private Position getAlphaPosition(List<Krill> herd,Krill krill, HerdParameters parameters)
{
Position alphaPosition = alphaCalculator.calculateAlpha(herd,krill,parameters);
return alphaPosition * parameters.N_MAX;
}
private void crossKrill(Krill toCross, List <Krill> herd)
{
int ind = Random.Range(0, herd.Count);
// toCross.crossover(herd[ind]);
}
public void TestKrill()
{
Krill krill = new Krill();
Assert.Equal("Krill are food for whales!", krill.BeEaten());
}
