org.uncommons.watchmaker.framework.operators
Class ListInversion<T>

java.lang.Object
  org.uncommons.watchmaker.framework.operators.ListInversion<T>

Type Parameters:

T - The type of entity being evolved.

All Implemented Interfaces:

EvolutionaryOperator<List<T>>

public class ListInversion<T>
extends Object
implements EvolutionaryOperator<List<T>>

An evolutionary operator that randomly reverses a subsection of a list.

Author:

Daniel Dyer

Constructor Summary

ListInversion(NumberGenerator<Probability> inversionProbability)

ListInversion(Probability inversionProbability)

Method Summary

List<List<T>>

apply(List<List<T>> selectedCandidates, Random rng) Apply the operation to each entry in the list of selected candidates.

Methods inherited from class java.lang.Object

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

Constructor Detail

ListInversion

public ListInversion(Probability inversionProbability)

Parameters:

inversionProbability - The probability that an individual list will have some subsection inverted.

ListInversion

public ListInversion(NumberGenerator<Probability> inversionProbability)

Parameters:

inversionProbability - A variable that controls the probability that an individual list will have some subsection inverted.

Method Detail

apply

public List<List<T>> apply(List<List<T>> selectedCandidates,
                           Random rng)

Description copied from interface: EvolutionaryOperator

Apply the operation to each entry in the list of selected candidates. It is important to note that this method operates on the list of candidates returned by the selection strategy and not on the current population. Each entry in the list (not each individual - the list may contain the same individual more than once) must be operated on exactly once.

Implementing classes should not assume any particular ordering (or lack of ordering) for the selection. If ordering or shuffling is required, it should be performed by the implementing class. The implementation should not re-order the list provided but instead should make a copy of the list and re-order that. The ordering of the selection should be totally irrelevant for operators that process each candidate in isolation, such as mutation. It should only be an issue for operators, such as cross-over, that deal with multiple candidates in a single operation.

The operator should not modify any of the candidates passed in. Instead it should return a list that contains evolved copies of those candidates (umodified candidates can be included in the results without having to be copied).

Specified by:

apply in interface EvolutionaryOperator<List<T>>

Parameters:

selectedCandidates - The individuals to evolve.

rng - A source of randomness for stochastic operators (most operators will be stochastic).

Returns:

The evolved individuals.