/// Best score (regardless of generation)

/// Label that displays the best score (bestScore attribute)

if generationCounter>=3{

// Experiment: Keep some of the last best birds and put them back into the population

lastBestGen=(flappyBirdGenerationContainer?.filter({$0.fitness>=9.0}))!

lastBestGen=(flappyBirdGenerationContainer?.filter({$0.fitness>=7.0}))!

if(currentBird?.fitness)!> maxFitness{

varoffspring=BiologicalProcessManager.onePointCrossover(crossoverRate:0.5, parentOneGenotype: parents.0.genotypeRepresentation, parentTwoGenotype: parents.1.genotypeRepresentation)

// Mutate their genes

BiologicalProcessManager.scrambleMutation(mutationRate:0.7, genotype:&offspring.0)

BiologicalProcessManager.scrambleMutation(mutationRate:0.7, genotype:&offspring.1)

BiologicalProcessManager.inverseMutation(mutationRate:0.7, genotype:&offspring.0)

BiologicalProcessManager.inverseMutation(mutationRate:0.7, genotype:&offspring.1)

// Create a separate neural network for the birds based on their genes

case softsign /// SoftSign Activation Function

case sinusoid /// Sinusoid Activation Function

case gaussian /// Sinusoid Activation Function

case ReLU /// ReLU Activation Function

case LeakyReLU /// Leaky ReLU Activation Function

/**

The activate method returns an activation function.

/**

The activate method returns the derivative of the activation function a Layer object is using.

Note that a Layer object is instantiated with an ActivationFunctionType. This method simply observes the

ActivationFunctionType that the layer is using and returns the derivative for that layers particular ActivationFunctionType.

- returns: A method that taeks in a Float as a parameter and returns a Float.

*/

returnexp(powf((-val),2))

privatefunc fncReLU(val:Float)->Float{

returnmax(0, val)

privatefunc fncLeakyReLU(val:Float)->Float{

returnmax(0.01*val, val)

// MARK: Derivatives

privatefunc derivativeOfLinear(val:Float)->Float{

return-2* val* exp(powf((-val),2))

privatefunc derivativeOfReLU(val:Float)->Float{

return(val<0.0)?0.0:1.0

privatefunc derivativeOfLeakyReLU(val:Float)->Float{

return(val<0.0)?0.01:1.0

/// Simply a method to satisfy the switch statements located in the activate and derivative methods. The method simply returns -1 which indicates that an error has occurred (A non-existant enum was discovered).

privatefunc error(val:Float)->Float{