Class RuleCrossoverPipeline
- All Implemented Interfaces:
Prototype,Setup,SteadyStateBSourceForm,RandomChoiceChooserD,Serializable,Cloneable
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
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Field Summary
FieldsModifier and TypeFieldDescriptionstatic final intstatic final Stringstatic final intstatic final Stringstatic final Stringstatic final StringdoubleWhat is the probability of a rule migrating?booleanShould the pipeline discard the second parent after crossing over?Fields inherited from class ec.BreedingPipeline
DYNAMIC_SOURCES, likelihood, mybase, P_LIKELIHOOD, P_NUMSOURCES, P_SOURCE, sources, V_SAME, V_STUBFields inherited from class ec.BreedingSource
NO_PROBABILITY, P_PROB, probability -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionclone()Creates a new individual cloned from a prototype, and suitable to begin use in its own evolutionary context.Returns the default base for this prototype.intReturns 2intproduce(int min, int max, int subpopulation, ArrayList<Individual> inds, EvolutionState state, int thread, HashMap<String, Object> misc) 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.voidsetup(EvolutionState state, Parameter base) Sets up the BreedingPipeline.intReturns 2 (unless tossing the second sibling, in which case it returns 1)Methods inherited from class ec.BreedingPipeline
fillStubs, finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, produces, sourcesAreProperFormMethods inherited from class ec.BreedingSource
getProbability, pickRandom, setProbability, setupProbabilities
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Field Details
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P_TOSS
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P_CROSSOVER
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P_CROSSOVERPROB
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INDS_PRODUCED
public static final int INDS_PRODUCED- See Also:
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NUM_SOURCES
public static final int NUM_SOURCES- See Also:
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KEY_PARENTS
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tossSecondParent
public boolean tossSecondParentShould the pipeline discard the second parent after crossing over? -
ruleCrossProbability
public double ruleCrossProbabilityWhat is the probability of a rule migrating?
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Constructor Details
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RuleCrossoverPipeline
public RuleCrossoverPipeline()
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Method Details
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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(...). -
numSources
public int numSources()Returns 2- Specified by:
numSourcesin classBreedingPipeline
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clone
Description copied from interface:PrototypeCreates 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 Populations, or Subpopulation.
- 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:
clonein interfacePrototype- Overrides:
clonein classBreedingPipeline
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setup
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}.
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typicalIndsProduced
public int typicalIndsProduced()Returns 2 (unless tossing the second sibling, in which case it returns 1)- Overrides:
typicalIndsProducedin classBreedingPipeline
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produce
public int produce(int min, int max, int subpopulation, ArrayList<Individual> inds, EvolutionState state, int thread, HashMap<String, Object> misc) Description copied from class:BreedingSourceProduces 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:
producein classBreedingSource
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