Module de.learnlib.algorithm.aaar

Package de.learnlib.algorithm.aaar.generic

Class GenericAAARLearnerDFA<L extends LearningAlgorithm.DFALearner<CI> & net.automatalib.alphabet.SupportsGrowingAlphabet<CI>,AI,CI>

java.lang.Object

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

de.learnlib.algorithm.aaar.generic.AbstractGenericAAARLearner<L,net.automatalib.automaton.fsa.DFA<?,AI>,net.automatalib.automaton.fsa.DFA<?,CI>,AI,CI,Boolean>

de.learnlib.algorithm.aaar.generic.GenericAAARLearnerDFA<L,AI,CI>

Type Parameters:

L - learner type

AI - abstract input symbol type

CI - concrete input symbol type

All Implemented Interfaces:

LearningAlgorithm<net.automatalib.automaton.fsa.DFA<?,AI>,CI,Boolean>

public class GenericAAARLearnerDFA<L extends LearningAlgorithm.DFALearner<CI> & net.automatalib.alphabet.SupportsGrowingAlphabet<CI>,AI,CI>
extends AbstractGenericAAARLearner<L,net.automatalib.automaton.fsa.DFA<?,AI>,net.automatalib.automaton.fsa.DFA<?,CI>,AI,CI,Boolean>

A DFA-specific refinement of AbstractGenericAAARLearner.

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
GenericAAARLearnerDFA(LearnerConstructor<L,CI,Boolean> learnerConstructor, MembershipOracle<CI,Boolean> oracle, CI initialConcrete, Function<CI,AI> abstractor)	Constructor.

Method Summary

Modifier and Type	Method	Description
net.automatalib.automaton.fsa.DFA<?,AI>	getHypothesisModel()	Returns the current hypothesis model.
net.automatalib.automaton.fsa.DFA<?,CI>	getTranslatingHypothesisModel()	Returns a model of the current internal hypothesis model (cf.

Methods inherited from class de.learnlib.algorithm.aaar.generic.AbstractGenericAAARLearner

getAbstractionTree, 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

GenericAAARLearnerDFA

public GenericAAARLearnerDFA(LearnerConstructor<L,CI,Boolean> learnerConstructor,
                             MembershipOracle<CI,Boolean> oracle,
                             CI initialConcrete,
                             Function<CI,AI> abstractor)

Constructor.

Parameters:

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

oracle - the (concrete) membership oracle

initialConcrete - the initial (concrete) input symbol used for starting the learning process

abstractor - the function for creating new abstract input symbols given concrete one. This function only receives input symbols from the provided (concrete) counterexamples

Method Detail

getHypothesisModel

public net.automatalib.automaton.fsa.DFA<?,AI> 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 should not be modified by external code (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 net.automatalib.automaton.fsa.DFA<?,CI> 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.DFALearner<CI> & net.automatalib.alphabet.SupportsGrowingAlphabet<CI>,net.automatalib.automaton.fsa.DFA<?,AI>,net.automatalib.automaton.fsa.DFA<?,CI>,AI,CI,Boolean>

Returns:

the (concrete) hypothesis model that automatically transforms input symbols