Module io.jenetics.ext

Package io.jenetics.ext

Class WeaselSelector<G extends Gene<?,G>,C extends Comparable<? super C>>

java.lang.Object

io.jenetics.ext.WeaselSelector<G,C>

Type Parameters:

G - the gene type

C - the fitness result type

All Implemented Interfaces:

Selector<G,C>

public class WeaselSelector<G extends Gene<?,G>,C extends Comparable<? super C>>
extends Object
implements Selector<G,C>

Selector implementation which is part of the Weasel program algorithm. The Weasel program is a thought experiment by Richard Dawkins to illustrate the functioning of the evolution: random mutation combined with non-random cumulative selection.

The selector always returns populations which only contains "count" instances of the best Phenotype.

Engine setup for the Weasel program:

final Engine<CharacterGene, Integer> engine = Engine.builder(problem) // Set the 'WeaselSelector'. .selector(new WeaselSelector<>()) // Disable survivors selector. .offspringFraction(1) // Set the 'WeaselMutator'. .alterers(new WeaselMutator<>(0.05)) .build();

Since:

3.5

Version:

5.0

See Also:

• Weasel program
• WeaselMutator

Constructor Summary

Constructors

Constructor	Description
WeaselSelector()

Method Summary

Modifier and Type	Method	Description
ISeq<Phenotype<G,C>>	select(Seq<Phenotype<G,C>> population, int count, Optimize opt)	Select phenotypes from the Population.
String	toString()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Details

WeaselSelector

public WeaselSelector()

Method Details

select

public ISeq<Phenotype<G,C>> select(Seq<Phenotype<G,C>> population,
 int count,
 Optimize opt)

Description copied from interface: Selector

Select phenotypes from the Population.

Specified by:

select in interface Selector<G extends Gene<?,G>,C extends Comparable<? super C>>

Parameters:

population - The population to select from.

count - The number of phenotypes to select.

opt - Determines whether the individuals with higher fitness values or lower fitness values must be selected. This parameter determines whether the GA maximizes or minimizes the fitness function.

Returns:

The selected phenotypes (a new Population).

toString

public String toString()

Overrides:

toString in class Object