fr.iscpif.mgo.problem

NoFitness

trait NoFitness extends Problem with MG

Linear Supertypes
fitness.MG, Problem, Evolution, elitism.Elitism, elitism.IndividualFilter, breed.Breeding, archive.Archive, archive.A, Lambda, termination.Termination, fitness.F, phenotype.P, genome.G, AnyRef, Any
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Inherited
  1. NoFitness
  2. MG
  3. Problem
  4. Evolution
  5. Elitism
  6. IndividualFilter
  7. Breeding
  8. Archive
  9. A
  10. Lambda
  11. Termination
  12. F
  13. P
  14. G
  15. AnyRef
  16. Any
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Type Members

  1. abstract type A

    Definition Classes
    Archive → A

  2. case class EvolutionState(population: Population[Evolution.G, Evolution.P, Evolution.F], archive: Evolution.A, generation: Int, terminationState: Evolution.STATE, terminated: Boolean) extends Product with Serializable

    Represent a state of the evolution algorithm

    Represent a state of the evolution algorithm

    Definition Classes
    Evolution

  3. type F = None.type

    Definition Classes
    NoFitness → F

  4. abstract type G

    Definition Classes
    G

  5. abstract type P

    Definition Classes
    P

  6. abstract type STATE

    Type of the state maintained to study the evolution of the algorithm

    Type of the state maintained to study the evolution of the algorithm

    Definition Classes
    Termination

Abstract Value Members

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

    Definition Classes
    Archive

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

    Definition Classes
    Breeding

  3. abstract def computeElitism(oldGeneration: Population[G, P, F], offspring: Population[G, P, F], archive: A)(implicit rng: Random): Population[G, P, F]

    Definition Classes
    Elitism

  4. abstract def express(g: G, rng: Random): P

    Definition Classes
    Problem

  5. abstract def initialArchive(implicit rng: Random): A

    Definition Classes
    Archive

  6. abstract def initialState: STATE

    Compute the initial state

    Compute the initial state

    returns

    the initial state

    Definition Classes
    Termination

  7. abstract def lambda: Int

    the size of the offspring

    the size of the offspring

    Definition Classes
    Lambda

  8. abstract def terminated(population: Population[G, P, F], terminationState: STATE)(implicit rng: Random): (Boolean, STATE)

    Test if the algorithm has converged.

    Test if the algorithm has converged.

    population

    the current population

    terminationState

    the actual termination state

    returns

    a boolean which is equal to true if a terminal state has been detected and the new termination state

    Definition Classes
    Termination

Concrete Value Members

  1. final def !=(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Definition Classes
    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  5. def buildRNG(seed: Long): Random

    Definition Classes
    Evolution

  6. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  7. def elitism(oldGeneration: Population[G, P, F], offspring: Population[G, P, F], archive: A)(implicit rng: Random): Population[G, P, F]

    Definition Classes
    Elitism

  8. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  9. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  10. def evaluate(phenotype: P, rng: Random): F

    Evaluate a phenotype

    Evaluate a phenotype

    phenotype

    the phenotype to evaluate

    returns

    the phenotype

    Definition Classes
    NoFitness → Problem

  11. def evolve(implicit rng: Random): Iterator[EvolutionState]

    Definition Classes
    Problem

  12. def evolve(expression: (G, Random) ⇒ P, evaluation: (P, Random) ⇒ F)(implicit prng: Random): Iterator[EvolutionState]

    Run the evolutionary algorithm

    Run the evolutionary algorithm

    expression

    the genome expression

    evaluation

    the fitness evaluator

    returns

    an iterator over the states of the evolution

    Definition Classes
    Evolution

  13. def evolve(population: Population[G, P, F], a: A, expression: (G, Random) ⇒ P, evaluation: (P, Random) ⇒ F)(implicit rng: Random): Iterator[EvolutionState]

    Run the evolutionary algorithm

    Run the evolutionary algorithm

    population

    the initial individuals

    expression

    the genome expression

    evaluation

    the fitness evaluator

    returns

    an iterator over the states of the evolution

    Definition Classes
    Evolution

  14. def filter(population: Population[G, P, F]): Population[G, P, F]

    Filter the individuals

    Filter the individuals

    population

    the set of evaluated individuals

    returns

    the filtrated individuals

    Definition Classes
    IndividualFilter

  15. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  16. def fitness(f: F): Seq[Nothing]

    Definition Classes
    NoFitness → MG

  17. def fitness(individual: Individual[G, P, F]): Seq[Double]

    Definition Classes
    MG

  18. def genomesEqualOn(g: G): Any

    Definition Classes
    G

  19. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  20. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  21. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  22. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  23. final def notify(): Unit

    Definition Classes
    AnyRef

  24. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  25. def step(population: Population[G, P, F], archive: A, expression: (G, Random) ⇒ P, evaluation: (P, Random) ⇒ F)(implicit rng: Random): (Population[G, P, F], A)

    Evolve one step

    Evolve one step

    population

    the current population

    archive

    the current archive

    expression

    expression of the genome

    evaluation

    the fitness evaluator

    returns

    a new population of evaluated solutions

    Definition Classes
    Evolution

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

    Definition Classes
    AnyRef

  27. def toString(): String

    Definition Classes
    AnyRef → Any

  28. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  30. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from fitness.MG

Inherited from Problem

Inherited from Evolution

Inherited from elitism.Elitism

Inherited from elitism.IndividualFilter

Inherited from breed.Breeding

Inherited from archive.Archive

Inherited from archive.A

Inherited from Lambda

Inherited from termination.Termination

Inherited from fitness.F

Inherited from phenotype.P

Inherited from genome.G

Inherited from AnyRef

Inherited from Any

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