Class RehangPipeline
- All Implemented Interfaces:
Prototype,Setup,SteadyStateBSourceForm,RandomChoiceChooserD,Serializable,Cloneable
Important Note: Because it must be free of any constraints by nature, RehangPipeline does not work with strong typing. You must not have more than one type defined in order to use RehangPipeline.
RehangPipeline picks a random tree, then picks randomly from all the nonterminals in the tree other than the root, and rehangs the chosen nonterminal as the new root. If its chosen tree has no nonterminals, it repeats the choose-tree process. If after tries times it has failed to find a tree with nonterminals (other than the root), it gives up and simply copies the individual. As you might guess, determining if a tree has nonterminals is very fast, so tries can be pretty large with little to no detriment to evolution speed.
"Rehanging" is complicated to describe. First, you pick a random child of your chosen nonterminal n, and remove this subtree from the tree. Call this subtree T. Next, you set the nonterminal as a new root; its former parent p now fills the slot left behind by the missing subtree. The p's former parent q now fills the slot left behind by n. q's former parent r now fills the slot left behind by p, and so on. This proceeds all the way up to the old root, which will be left with one empty slot (where its former child was that is now its new parent). This slot is then filled with T
Typical Number of Individuals Produced Per produce(...) call
...as many as the source produces
Number of Sources
1
Parameters
| base.tries int >= 1 |
(number of times to try finding valid pairs of nodes) |
| base.tree.0 0 < int < (num trees in individuals), if exists |
(tree chosen for mutation; if parameter doesn't exist, tree is picked at random) |
Default Base
gp.breed.rehang
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Field Summary
FieldsFields inherited from class ec.gp.GPBreedingPipeline
P_NODESELECTOR, P_TREE, TREE_UNFIXEDFields 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 TypeMethodDescriptionReturns the default base for this prototype.intReturns the number of sources to this pipeline.intproduce(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.Methods inherited from class ec.gp.GPBreedingPipeline
producesMethods inherited from class ec.BreedingPipeline
clone, fillStubs, finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, sourcesAreProperForm, typicalIndsProducedMethods inherited from class ec.BreedingSource
getProbability, pickRandom, setProbability, setupProbabilities
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Field Details
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P_REHANG
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P_NUM_TRIES
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NUM_SOURCES
public static final int NUM_SOURCES- See Also:
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Constructor Details
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RehangPipeline
public RehangPipeline()
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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()Description copied from class:BreedingPipelineReturns the number of sources to this pipeline. Called during BreedingPipeline's setup. Be sure to return a value > 0, or DYNAMIC_SOURCES which indicates that setup should check the parameter file for the parameter "num-sources" to make its determination.- Specified by:
numSourcesin 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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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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