Documentation of 'ec.rule.breed.RuleCrossoverPipeline' Java class
RuleCrossoverPipeline
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ec.rule.breed

Class RuleCrossoverPipeline

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

    public class RuleCrossoverPipeline
extends BreedingPipeline
    RuleCrossoverPipeline is a BreedingPipeline which implements a simple default crossover for RuleIndividuals. Normally it takes two individuals and returns two crossed-over child individuals. Optionally, it can take two individuals, cross them over, but throw away the second child (a one-child crossover). RuleCrossoverPipeline works by iteratively taking rulesets from each individual, and migrating rules from either to the other with a certain per-rule probability. Rule crossover preserves the min and max rule restrictions.

    Typical Number of Individuals Produced Per produce(...) call
    1 or 2

    Number of Sources
    2

    Parameters

    base.toss
    bool = true or false (default)/td>     		(after crossing over with the first new individual, should its second sibling individual be thrown away instead of adding it to the population?)
    base.prob
    0.0 <= double < 1.0, or 0.5 (default)/td>     		(probability that a rule will cross over from one individual to the other)

    Default Base
    rule.xover

    See Also:
    Serialized Form

    • Field Detail

      • tossSecondParent

        public boolean tossSecondParent
        Should the pipeline discard the second parent after crossing over?

      • ruleCrossProbability

        public double ruleCrossProbability
        What is the probability of a rule migrating?

    • Constructor Detail

      • RuleCrossoverPipeline

        public RuleCrossoverPipeline()

    • 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(...).

      • clone

        public java.lang.Object clone()
        Description copied from interface: Prototype
        Creates a new individual cloned from a prototype, and suitable to begin use in its own evolutionary context.

        Typically this should be a full "deep" clone. However, you may share certain elements with other objects rather than clone hem, depending on the situation:

        • If you hold objects which are shared with other instances, don't clone them.
        • If you hold objects which must be unique, clone them.
        • If you hold objects which were given to you as a gesture of kindness, and aren't owned by you, you probably shouldn't clone them.
        • DON'T attempt to clone: Singletons, Cliques, or Groups.
        • Arrays are not cloned automatically; you may need to clone an array if you're not sharing it with other instances. Arrays have the nice feature of being copyable by calling clone() on them.

        Implementations.

        • If no ancestor of yours implements clone(), and you have no need to do clone deeply, and you are abstract, then you should not declare clone().
        • If no ancestor of yours implements clone(), and you have no need to do clone deeply, and you are not abstract, then you should implement it as follows: 

           public Object clone() 
     {
     try
         { 
         return super.clone();
         }
     catch ((CloneNotSupportedException e)
         { throw new InternalError(); } // never happens
     }
        • If no ancestor of yours implements clone(), but you need to deep-clone some things, then you should implement it as follows: 

           public Object clone() 
     {
     try
         { 
         MyObject myobj = (MyObject) (super.clone());

         // put your deep-cloning code here...
         }
     catch ((CloneNotSupportedException e)
         { throw new InternalError(); } // never happens
     return myobj;
     }
        • If an ancestor has implemented clone(), and you also need to deep clone some things, then you should implement it as follows: 

           public Object clone() 
     { 
     MyObject myobj = (MyObject) (super.clone());

     // put your deep-cloning code here...

     return myobj;
     }
        Specified by:
        clone in interface Prototype
        Overrides:
        clone in class BreedingPipeline

      • 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 BreedingPipeline
        See Also:
        Prototype.setup(EvolutionState,Parameter)

      • typicalIndsProduced

        public int typicalIndsProduced()
        Returns 2 (unless tossing the second sibling, in which case it returns 1)
        Overrides:
        typicalIndsProduced in class BreedingPipeline

      • produce

        public int produce(int min,
                   int max,
                   int start,
                   int subpopulation,
                   Individual[] inds,
                   EvolutionState state,
                   int thread)
        Description copied from class: BreedingSource
        Produces n individuals from the given subpopulation and puts them into inds[start...start+n-1], where n = Min(Max(q,min),max), where q is the "typical" number of individuals the BreedingSource produces in one shot, and returns n. max must be >= min, and min must be >= 1. For example, crossover might typically produce two individuals, tournament selection might typically produce a single individual, etc.
        Specified by:
        produce in class BreedingSource
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