DynamicApplicationGA

Type Members

abstract type A

Definition Classes
Archive → A
type Ancestors = (F, F)

Definition Classes
DynamicApplicationGAGenome
trait CandidateCrossover extends Crossover
trait CandidateMutation extends Mutation
trait DAMethodInjection extends AnyRef
abstract type F

Definition Classes
F
type G = Genome

Definition Classes
DynamicApplicationGAGenome → G
case class Genome(values: Seq[Double], sigma: Seq[Double], ancestors: Option[Ancestors] = None, mutation: Option[Int] = None, crossover: Option[Int] = None) extends Product with Serializable

Definition Classes
DynamicApplicationGAGenome
abstract type P

Definition Classes
P

Abstract Value Members

abstract def archive(a: A, oldIndividuals: Population[G, P, F], offspring: Population[G, P, F])(implicit rng: Random): A

Definition Classes
Archive
abstract def clamp(values: SimpleLens[G, Seq[Double]]): SimpleLens[G, Seq[Double]]

Definition Classes
GenomeClamping
abstract def genomeSize: Int

Size of the value part of the genome
Size of the value part of the genome

Definition Classes
GA
abstract def initialArchive(implicit rng: Random): A

Definition Classes
Archive
abstract def selection(population: Population[G, P, F], archive: A)(implicit rng: Random): Iterator[Individual[G, P, F]]

Select an individual among the population.
Select an individual among the population.
param population the population in which selection occurs
returns
the selected individual

Definition Classes
Selection

Concrete Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
lazy val adaptiveCauchy: AdaptiveCauchyMutation with CandidateMutation with DAMethodInjection
def ancestors: Lens[G, G, Option[Ancestors], Option[Ancestors]]

Definition Classes
DynamicApplicationGAGenome
final def asInstanceOf[T0]: T0

Definition Classes
Any
lazy val bga: BGAMutation with CandidateMutation with DAMethodInjection
lazy val bigbga: BGAMutation with CandidateMutation with DAMethodInjection
lazy val blx: BLXCrossover with CandidateCrossover with DAMethodInjection
def breed(i1: Individual[G, P, F], i2: Individual[G, P, F], population: Population[G, P, F], a: A)(implicit rng: Random): Seq[G]

Definition Classes
DynamicApplicationGA → GeneticBreeding
def breed(population: Population[G, P, F], a: A, size: Int)(implicit rng: Random): Seq[G]

Breed genomes from a population
Breed genomes from a population
population
the population from which genomes are breeded
size
the size of the breeded set
returns
the breeded genomes

Definition Classes
GeneticBreeding → Breeding
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def cloneProbability: Double

Definition Classes
GeneticBreeding
def crossover(g1: G, g2: G, population: Population[G, P, F], archive: A)(implicit rng: Random): Seq[G]

Crossover g1 and g2
Crossover g1 and g2
g1
a genome
g2
another genome
population
last computed population
archive
last archive
returns
the result of the crossover

Definition Classes
DynamicApplicationGA → Crossover
def crossover: Lens[G, G, Option[Int], Option[Int]]

Definition Classes
DynamicApplicationGAGenome
def crossoverStats(p: Population[G, P, F]): scala.collection.Map[Int, Double]
def crossovers: Seq[CandidateCrossover]
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
def genomesEqualOn(g: G): Any

Definition Classes
GA → G
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def hashCode(): Int

Definition Classes
AnyRef → Any
lazy val idc: IdentityCrossOver with CandidateCrossover with DAMethodInjection
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def mutate(g: G, population: Population[G, P, F], archive: A)(implicit rng: Random): G

Mutate a genome
Mutate a genome
population
the last computed population
archive
the last archive
rng
a random number geneartor
returns
the mutated genome

Definition Classes
DynamicApplicationGA → Mutation
def mutation: Lens[G, G, Option[Int], Option[Int]]

Definition Classes
DynamicApplicationGAGenome
def mutationStats(p: Population[G, P, F]): scala.collection.Map[Int, Double]
def mutations: Seq[CandidateMutation]
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def operatorExploration: Double
def randomGenome(implicit rng: Random): Genome

Definition Classes
DynamicApplicationGAGenome → GA → RandomGenome
def rawValues: Lens[G, G, Seq[Double], Seq[Double]]

Definition Classes
DynamicApplicationGAGenome → GA
lazy val sbx: SBXCrossover with CandidateCrossover with DAMethodInjection
def sigma: Lens[G, G, Seq[Double], Seq[Double]]

Definition Classes
DynamicApplicationGAGenome → Sigma
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
def values: SimpleLens[G, Seq[Double]]

The value part of the genome actually used for the optimisation
The value part of the genome actually used for the optimisation

Definition Classes
GA
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

trait DynamicApplicationGA extends Crossover with Mutation with DynamicApplicationGAGenome with GeneticBreeding

Type Members

abstract type A

type Ancestors = (F, F)

trait CandidateCrossover extends Crossover

trait CandidateMutation extends Mutation

trait DAMethodInjection extends AnyRef

abstract type F

type G = Genome

case class Genome(values: Seq[Double], sigma: Seq[Double], ancestors: Option[Ancestors] = None, mutation: Option[Int] = None, crossover: Option[Int] = None) extends Product with Serializable

abstract type P

Abstract Value Members

abstract def archive(a: A, oldIndividuals: Population[G, P, F], offspring: Population[G, P, F])(implicit rng: Random): A

abstract def clamp(values: SimpleLens[G, Seq[Double]]): SimpleLens[G, Seq[Double]]

abstract def genomeSize: Int

abstract def initialArchive(implicit rng: Random): A

abstract def selection(population: Population[G, P, F], archive: A)(implicit rng: Random): Iterator[Individual[G, P, F]]

Concrete Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

lazy val adaptiveCauchy: AdaptiveCauchyMutation with CandidateMutation with DAMethodInjection

def ancestors: Lens[G, G, Option[Ancestors], Option[Ancestors]]

final def asInstanceOf[T0]: T0

lazy val bga: BGAMutation with CandidateMutation with DAMethodInjection

lazy val bigbga: BGAMutation with CandidateMutation with DAMethodInjection

lazy val blx: BLXCrossover with CandidateCrossover with DAMethodInjection

def breed(i1: Individual[G, P, F], i2: Individual[G, P, F], population: Population[G, P, F], a: A)(implicit rng: Random): Seq[G]

def breed(population: Population[G, P, F], a: A, size: Int)(implicit rng: Random): Seq[G]

def clone(): AnyRef

def cloneProbability: Double

def crossover(g1: G, g2: G, population: Population[G, P, F], archive: A)(implicit rng: Random): Seq[G]

def crossover: Lens[G, G, Option[Int], Option[Int]]

def crossoverStats(p: Population[G, P, F]): scala.collection.Map[Int, Double]

def crossovers: Seq[CandidateCrossover]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

def genomesEqualOn(g: G): Any

final def getClass(): Class[_]

def hashCode(): Int

lazy val idc: IdentityCrossOver with CandidateCrossover with DAMethodInjection

final def isInstanceOf[T0]: Boolean

def mutate(g: G, population: Population[G, P, F], archive: A)(implicit rng: Random): G

def mutation: Lens[G, G, Option[Int], Option[Int]]

def mutationStats(p: Population[G, P, F]): scala.collection.Map[Int, Double]

def mutations: Seq[CandidateMutation]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def operatorExploration: Double

def randomGenome(implicit rng: Random): Genome

def rawValues: Lens[G, G, Seq[Double], Seq[Double]]

lazy val sbx: SBXCrossover with CandidateCrossover with DAMethodInjection

def sigma: Lens[G, G, Seq[Double], Seq[Double]]

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

def values: SimpleLens[G, Seq[Double]]

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from breed.GeneticBreeding

Inherited from selection.Selection

Inherited from breed.Breeding

Inherited from archive.Archive

Inherited from DynamicApplicationGAGenome

Inherited from genome.Sigma

Inherited from genome.GA

Inherited from GenomeClamping

Inherited from RandomGenome

Inherited from mutation.Mutation

Inherited from crossover.Crossover

Inherited from archive.A

Inherited from fitness.F

Inherited from phenotype.P

Inherited from genome.G

Inherited from AnyRef

Inherited from Any

Ungrouped