Class BoltzmannSelection
- java.lang.Object
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- ec.BreedingSource
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- ec.SelectionMethod
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- ec.select.FitProportionateSelection
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- ec.select.BoltzmannSelection
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- 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
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Field Summary
Fields Modifier and Type Field and Description static java.lang.StringP_BOLTZMANNDefault basestatic java.lang.StringP_COOLING_RATECooling rate parameterstatic java.lang.StringP_STARTING_TEMPERATUREStarting temperature parameter-
Fields inherited from class ec.select.FitProportionateSelection
fitnesses, P_FITNESSPROPORTIONATE
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Fields inherited from class ec.SelectionMethod
INDS_PRODUCED
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Fields inherited from class ec.BreedingSource
NO_PROBABILITY, P_PROB, probability
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Constructor Summary
Constructors Constructor and Description BoltzmannSelection()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description ParameterdefaultBase()Returns the default base for this prototype.voidprepareToProduce(EvolutionState s, int subpopulation, int thread)A default version of prepareToProduce which does nothing.voidsetup(EvolutionState state, Parameter base)Sets up the BreedingPipeline.-
Methods inherited from class ec.select.FitProportionateSelection
finishProducing, produce
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Methods inherited from class ec.SelectionMethod
produce, produces, typicalIndsProduced
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Methods inherited from class ec.BreedingSource
clone, getProbability, pickRandom, preparePipeline, setProbability, setupProbabilities
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Field Detail
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P_BOLTZMANN
public static final java.lang.String P_BOLTZMANN
Default base- See Also:
- Constant Field Values
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P_STARTING_TEMPERATURE
public static final java.lang.String P_STARTING_TEMPERATURE
Starting temperature parameter- See Also:
- Constant Field Values
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P_COOLING_RATE
public static final java.lang.String P_COOLING_RATE
Cooling rate parameter- See Also:
- Constant Field Values
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Method Detail
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defaultBase
public Parameter defaultBase()
Description copied from interface:PrototypeReturns 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:
defaultBasein interfacePrototype- Overrides:
defaultBasein classFitProportionateSelection
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setup
public void setup(EvolutionState state, Parameter base)
Description copied from class:BreedingSourceSets 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:
setupin interfacePrototype- Specified by:
setupin interfaceSetup- Overrides:
setupin classBreedingSource- See Also:
Prototype.setup(EvolutionState,Parameter)
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prepareToProduce
public void prepareToProduce(EvolutionState s, int subpopulation, int thread)
Description copied from class:SelectionMethodA default version of prepareToProduce which does nothing.- Overrides:
prepareToProducein classFitProportionateSelection
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