Package de.learnlib.algorithm.aaar.explicit

Class ExplicitAAARLearnerMoore<L extends LearningAlgorithm.MooreLearner<CI,O> & SupportsGrowingAlphabet<CI>,AI,CI,O>

java.lang.Object

de.learnlib.algorithm.aaar.AbstractAAARLearner<L,AM,CM,AI,CI,D>

de.learnlib.algorithm.aaar.explicit.AbstractExplicitAAARLearner<L,MooreMachine<?,AI,?,O>,MooreMachine<?,CI,?,O>,AI,CI,Word<O>>

de.learnlib.algorithm.aaar.explicit.ExplicitAAARLearnerMoore<L,AI,CI,O>

Type Parameters:

L - learner type

AI - abstract input symbol type

CI - concrete input symbol type

O - output symbol type

All Implemented Interfaces:

LearningAlgorithm<MooreMachine<?,AI,?,O>,CI,Word<O>>

public class ExplicitAAARLearnerMoore<L extends LearningAlgorithm.MooreLearner<CI,O> & SupportsGrowingAlphabet<CI>,AI,CI,O>
extends AbstractExplicitAAARLearner<L,MooreMachine<?,AI,?,O>,MooreMachine<?,CI,?,O>,AI,CI,Word<O>>

A LearningAlgorithm.MooreLearner-specific refinement of AbstractExplicitAAARLearner.

Nested Class Summary

Nested classes/interfaces inherited from interface de.learnlib.algorithm.LearningAlgorithm

LearningAlgorithm.DFALearner<I>, LearningAlgorithm.MealyLearner<I,O>, LearningAlgorithm.MooreLearner<I,O>, LearningAlgorithm.NFALearner<I>

Constructor Summary

Constructors

Constructor	Description
ExplicitAAARLearnerMoore(LearnerConstructor<L,CI,Word<O>> learnerConstructor, MembershipOracle<CI,Word<O>> oracle, ExplicitInitialAbstraction<AI,CI> explicitInitialAbstraction, Function<AI,AI> incrementor)	Constructor.

Method Summary

Modifier and Type	Method	Description
MooreMachine<?,AI,?,O>	getHypothesisModel()	Returns the current hypothesis model.
MooreMachine<?,CI,?,O>	getTranslatingHypothesisModel()	Returns a model of the current internal hypothesis model (cf.

Methods inherited from class de.learnlib.algorithm.aaar.explicit.AbstractExplicitAAARLearner

getAbstractionTrees, getInitialAbstracts, getInitialRepresentatives, getLearnerAlphabet, getTreeForRepresentative

Methods inherited from class de.learnlib.algorithm.aaar.AbstractAAARLearner

copyAbstract, getAbstractAlphabet, getLearner, getLearnerHypothesisModel, refineHypothesis, startLearning

Methods inherited from class java.lang.Object

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

Constructor Detail

ExplicitAAARLearnerMoore

public ExplicitAAARLearnerMoore(LearnerConstructor<L,CI,Word<O>> learnerConstructor,
                                MembershipOracle<CI,Word<O>> oracle,
                                ExplicitInitialAbstraction<AI,CI> explicitInitialAbstraction,
                                Function<AI,AI> incrementor)

Constructor.

Parameters:

learnerConstructor - the provider for constructing the internal (concrete) learner

oracle - the (concrete) membership oracle

explicitInitialAbstraction - the initial mapping between concrete and abstract input symbols

incrementor - the function for creating new abstract input symbols given concrete one. This function only receives input symbols from the provided explicitInitialAbstraction

Method Detail

getHypothesisModel

public MooreMachine<?,AI,?,O> getHypothesisModel()

Description copied from interface: LearningAlgorithm

Returns the current hypothesis model.

N.B.: By the contract of this interface, the model returned by this method may not be modified (i.e., M generally should refer to an immutable interface), and its validity is retained only until the next invocation of LearningAlgorithm.refineHypothesis(DefaultQuery). If older hypotheses have to be maintained, a copy of the returned model must be made.

Please note that it should be illegal to invoke this method before an initial invocation of LearningAlgorithm.startLearning().

Returns:

the current hypothesis model.

getTranslatingHypothesisModel

public MooreMachine<?,CI,?,O> getTranslatingHypothesisModel()

Description copied from class: AbstractAAARLearner

Returns a model of the current internal hypothesis model (cf. AbstractAAARLearner.getLearnerHypothesisModel()) that automatically transforms (concrete) input symbols to abstract ones and uses their representatives to actually perform transitions. This allows the returned model to handle (concrete) input symbols that have not yet been added to the hypothesis by previous abstraction refinements. Note that this model requires the MembershipOracle passed to the constructor of this learner to still function in order to determine the abstract input symbols.

Specified by:

getTranslatingHypothesisModel in class AbstractAAARLearner<L extends LearningAlgorithm.MooreLearner<CI,O> & SupportsGrowingAlphabet<CI>,MooreMachine<?,AI,?,O>,MooreMachine<?,CI,?,O>,AI,CI,Word<O>>

Returns:

the (concrete) hypothesis model that automatically transforms input symbols