Package de.learnlib.algorithm

Interface PassiveLearningAlgorithm<M,I,D>

All Known Subinterfaces:

PassiveLearningAlgorithm.PassiveAcceptorLearner<M,I>, PassiveLearningAlgorithm.PassiveDFALearner<I>, PassiveLearningAlgorithm.PassiveMealyLearner<I,O>, PassiveLearningAlgorithm.PassiveMooreLearner<I,O>

public interface PassiveLearningAlgorithm<M,I,D>

Nested Class Summary

Nested Classes

Modifier and Type	Interface	Description
static interface	PassiveLearningAlgorithm.PassiveAcceptorLearner<M extends FiniteStateAcceptor<?,I>,I>	Basic interface for passive learning algorithms that infer finite-state acceptors (DFAs or NFAs).
static interface	PassiveLearningAlgorithm.PassiveDFALearner<I>	Basic interface for passive learning algorithms that infer DFAs.
static interface	PassiveLearningAlgorithm.PassiveMealyLearner<I,O>	Basic interface for passive learning algorithms that infer Mealy machines.
static interface	PassiveLearningAlgorithm.PassiveMooreLearner<I,O>	Basic interface for passive learning algorithms that infer Moore machines.

Method Summary

Modifier and Type	Method	Description
default void	addSample(DefaultQuery<I,D> sample)
default void	addSample(Word<I> input, D output)
default void	addSamples(DefaultQuery<I,D>... samples)
default void	addSamples(D output, Collection<? extends Word<I>> words)
default void	addSamples(D output, Word<I>... words)
void	addSamples(Collection<? extends DefaultQuery<I,D>> samples)
M	computeModel()	Computes the model given the previously added samples.

Method Detail

addSamples

void addSamples(Collection<? extends DefaultQuery<I,D>> samples)

addSamples

default void addSamples(DefaultQuery<I,D>... samples)

addSamples

default void addSamples(D output,
                        Word<I>... words)

addSamples

default void addSamples(D output,
                        Collection<? extends Word<I>> words)

addSample

default void addSample(Word<I> input,
                       D output)

addSample

default void addSample(DefaultQuery<I,D> sample)

computeModel

M computeModel()

Computes the model given the previously added samples.

Implementation note: It is up to the implementation if this operation is repeatable or not, An implementation may throw an IllegalStateException if additional samples are added after the first model construction.

Returns:

the computed model