Documentation of 'ec.select.BoltzmannSelection' Java class
BoltzmannSelection
ec.select

Class BoltzmannSelection

  • All Implemented Interfaces:
    Prototype, Setup, RandomChoiceChooserD, java.io.Serializable, java.lang.Cloneable


    public class BoltzmannSelection
    extends FitProportionateSelection
    Similar to FitProportionateSelection, but with a Simulated Annealing style twist. BoltzmannSelection picks individuals of a population in proportion to an adjusted version of their fitnesses instead of their actual fitnesses as returned by fitness(). The adjusted fitness is calculated by e^(fitness/current_temperature) where current_temperature is a temperature value that decreases by a constant cooling rate as generations of evolution pass. The current_temperature is calculated by starting-temperature - (cooling-rate * the_current_generation_number). When the temperature dips below 1.0, annealing ceases and BoltzmannSelection reverts to normal FitProportionateSelection behavior.

    Like FitProportionateSelection this is not appropriate for steady-state evolution. If you're not familiar with the relative advantages of selection methods and just want a good one, use TournamentSelection instead. Not appropriate for multiobjective fitnesses.

    Note: Fitnesses must be non-negative. 0 is assumed to be the worst fitness.

    Typical Number of Individuals Produced Per produce(...) call
    Always 1.

    Parameters

    base.starting-temperature
    double = some large number (defaults to 1.0)
    (the starting temperature for our simulated annealing style adjusted fitness proportions)
    base.cooling-rate
    double = some smaller number (defaults to 0.0 which causes BoltzmannSelection to behave just as FitProportionateSelection would)
    (how slow, or fast, do you want to cool the annealing fitness proportions?)

    Default Base
    select.boltzmann

    See Also:
    Serialized Form
    • Field Detail

      • P_BOLTZMANN

        public static final java.lang.String P_BOLTZMANN
        Default base
        See Also:
        Constant Field Values
      • P_STARTING_TEMPERATURE

        public static final java.lang.String P_STARTING_TEMPERATURE
        Starting temperature parameter
        See Also:
        Constant Field Values
      • P_COOLING_RATE

        public static final java.lang.String P_COOLING_RATE
        Cooling rate parameter
        See Also:
        Constant Field Values
    • Constructor Detail

      • BoltzmannSelection

        public BoltzmannSelection()
    • Method Detail

      • defaultBase

        public Parameter defaultBase()
        Description copied from interface: Prototype
        Returns the default base for this prototype. This should generally be implemented by building off of the static base() method on the DefaultsForm object for the prototype's package. This should be callable during setup(...).
        Specified by:
        defaultBase in interface Prototype
        Overrides:
        defaultBase in class FitProportionateSelection
      • setup

        public void setup(EvolutionState state,
                          Parameter base)
        Description copied from class: BreedingSource
        Sets up the BreedingPipeline. You can use state.output.error here because the top-level caller promises to call exitIfErrors() after calling setup. Note that probability might get modified again by an external source if it doesn't normalize right.

        The most common modification is to normalize it with some other set of probabilities, then set all of them up in increasing summation; this allows the use of the fast static BreedingSource-picking utility method, BreedingSource.pickRandom(...). In order to use this method, for example, if four breeding source probabilities are {0.3, 0.2, 0.1, 0.4}, then they should get normalized and summed by the outside owners as: {0.3, 0.5, 0.6, 1.0}.

        Specified by:
        setup in interface Prototype
        Specified by:
        setup in interface Setup
        Overrides:
        setup in class BreedingSource
        See Also:
        Prototype.setup(EvolutionState,Parameter)

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