Class GreedyOverselection
- java.lang.Object
-
- ec.BreedingSource
-
- ec.SelectionMethod
-
- ec.select.GreedyOverselection
-
- All Implemented Interfaces:
- Prototype, Setup, RandomChoiceChooserD, java.io.Serializable, java.lang.Cloneable
public class GreedyOverselection extends SelectionMethod
GreedyOverselection is a SelectionMethod which implements Koza-style fitness-proportionate greedy overselection. Not appropriate for multiobjective fitnesses.This selection method first divides individuals in a population into two groups: the "good" ("top") group, and the "bad" ("bottom") group. The best top percent of individuals in the population go into the good group. The rest go into the "bad" group. With a certain probability (determined by the gets setting), an individual will be picked out of the "good" group. Once we have determined which group the individual will be selected from, the individual is picked using fitness proportionate selection in that group, that is, the likelihood he is picked is proportionate to his fitness relative to the fitnesses of others in his group.
All this is expensive to set up and bring down, so it's 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.
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.top
0.0 <= double <= 1.0(the percentage of the population going into the "good" (top) group) base.gets
0.0 <= double <= 1.0(the likelihood that an individual will be picked from the "good" group) Default Base
select.greedy- See Also:
- Serialized Form
-
-
Field Summary
Fields Modifier and Type Field and Description doublegets_n_percentstatic java.lang.StringP_GETSstatic java.lang.StringP_GREEDYstatic java.lang.StringP_TOPdouble[]sortedFitOverdouble[]sortedFitUnderint[]sortedPopSorted population -- since I *have* to use an int-sized individual (short gives me only 16K), I might as well just have pointers to the population itself.doubletop_n_percent-
Fields inherited from class ec.SelectionMethod
INDS_PRODUCED
-
Fields inherited from class ec.BreedingSource
NO_PROBABILITY, P_PROB, probability
-
-
Constructor Summary
Constructors Constructor and Description GreedyOverselection()
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description ParameterdefaultBase()Returns the default base for this prototype.voidfinishProducing(EvolutionState s, int subpopulation, int thread)A default version of finishProducing, which does nothing.voidprepareToProduce(EvolutionState s, int subpopulation, int thread)A default version of prepareToProduce which does nothing.intproduce(int subpopulation, EvolutionState state, int thread)An alternative form of "produce" special to Selection Methods; selects an individual from the given subpopulation and returns its position in that subpopulation.voidsetup(EvolutionState state, Parameter base)Sets up the BreedingPipeline.-
Methods inherited from class ec.SelectionMethod
produce, produces, typicalIndsProduced
-
Methods inherited from class ec.BreedingSource
clone, getProbability, pickRandom, preparePipeline, setProbability, setupProbabilities
-
-
-
-
Field Detail
-
sortedFitOver
public double[] sortedFitOver
-
sortedFitUnder
public double[] sortedFitUnder
-
sortedPop
public int[] sortedPop
Sorted population -- since I *have* to use an int-sized individual (short gives me only 16K), I might as well just have pointers to the population itself. :-(
-
P_GREEDY
public static final java.lang.String P_GREEDY
- See Also:
- Constant Field Values
-
P_TOP
public static final java.lang.String P_TOP
- See Also:
- Constant Field Values
-
P_GETS
public static final java.lang.String P_GETS
- See Also:
- Constant Field Values
-
top_n_percent
public double top_n_percent
-
gets_n_percent
public double gets_n_percent
-
-
Method Detail
-
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(...).
-
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)
-
prepareToProduce
public void prepareToProduce(EvolutionState s, int subpopulation, int thread)
Description copied from class:SelectionMethodA default version of prepareToProduce which does nothing.- Overrides:
prepareToProducein classSelectionMethod
-
produce
public int produce(int subpopulation, EvolutionState state, int thread)Description copied from class:SelectionMethodAn alternative form of "produce" special to Selection Methods; selects an individual from the given subpopulation and returns its position in that subpopulation.- Specified by:
producein classSelectionMethod
-
finishProducing
public void finishProducing(EvolutionState s, int subpopulation, int thread)
Description copied from class:SelectionMethodA default version of finishProducing, which does nothing.- Overrides:
finishProducingin classSelectionMethod
-
-
DMelt 3.0 © DataMelt by jWork.ORG