NoisyOSEOperations
object NoisyOSEOperations
Value members
Concrete methods
def adaptiveBreeding[S, I, G, P](history: I => Vector[P], aggregation: Vector[P] => Vector[Double], genome: I => G, continuousValues: G => Vector[Double], continuousOperator: G => Option[Int], discreteValues: G => Vector[Int], discreteOperator: G => Option[Int], discrete: Vector[D], buildGenome: (Vector[Double], Option[Int], Vector[Int], Option[Int]) => G, tournamentRounds: Int => Int, lambda: Int, reject: Option[G => Boolean], operatorExploration: Double, cloneProbability: Double, origin: (Vector[Double], Vector[Int]) => Vector[Int], limit: Vector[Double], archive: S => Array[I], reachMap: S => ReachMap): (S, I) => G
def aggregated[I, P](fitness: I => Vector[P], aggregation: Vector[P] => Vector[Double])(i: I): Vector[Double]
def elitism[S, I : ClassTag, P](history: I => Vector[P], aggregation: Vector[P] => Vector[Double], values: I => (Vector[Double], Vector[Int]), origin: (Vector[Double], Vector[Int]) => Vector[Int], limit: Vector[Double], historySize: Int, mergeHistories: (Vector[I], Vector[I]) => Vector[I], mu: Int, archive: Lens[S, Array[I]], reachMap: Lens[S, ReachMap]): S => I
def promisingReachMap[I](fitness: I => Vector[Double], limit: Vector[Double], origin: I => Vector[Int], population: Vector[I]): Set[Vector[Int]]