Package de.learnlib.algorithm.ttt.moore

Class TTTLearnerMoore<I,O>

java.lang.Object

de.learnlib.algorithm.ttt.base.AbstractTTTLearner<MooreMachine<?,I,?,O>,I,Word<O>>

de.learnlib.algorithm.ttt.moore.TTTLearnerMoore<I,O>

Type Parameters:

I - input symbol type

O - output symbols type

All Implemented Interfaces:

LearningAlgorithm<MooreMachine<?,I,?,O>,I,Word<O>>, LearningAlgorithm.MooreLearner<I,O>, Resumable<TTTLearnerState<I,Word<O>>>, SupportsGrowingAlphabet<I>

public class TTTLearnerMoore<I,O>
extends AbstractTTTLearner<MooreMachine<?,I,?,O>,I,Word<O>>
implements LearningAlgorithm.MooreLearner<I,O>

A MooreMachine-based specialization of the TTT learner.

Nested Class Summary

Nested classes/interfaces inherited from class de.learnlib.algorithm.ttt.base.AbstractTTTLearner

AbstractTTTLearner.BuilderDefaults, AbstractTTTLearner.Splitter<I,D>

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

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

Field Summary

Fields inherited from class de.learnlib.algorithm.ttt.base.AbstractTTTLearner

alphabet, analyzer, blockList, dtree, hypothesis, openTransitions, oracle

Constructor Summary

Constructors

Constructor	Description
TTTLearnerMoore(Alphabet<I> alphabet, MembershipOracle<I,Word<O>> oracle, AcexAnalyzer analyzer)

Method Summary

Modifier and Type	Method	Description
protected Word<O>	computeHypothesisOutput(TTTState<I,Word<O>> state, Word<I> suffix)
protected AbstractBaseDTNode<I,Word<O>>	createNewNode(AbstractBaseDTNode<I,Word<O>> parent, Word<O> parentOutput)
protected OutInconsPrefixTransformAcex<I,Word<O>>	deriveAcex(OutputInconsistency<I,Word<O>> outIncons)
TTTHypothesisMoore<I,O>	getHypothesisModel()	Returns the current hypothesis model.
protected void	initializeState(TTTState<I,Word<O>> state)	Initializes a state.
protected Word<O>	predictSuccOutcome(TTTTransition<I,Word<O>> trans, AbstractBaseDTNode<I,Word<O>> succSeparator)
protected boolean	refineHypothesisSingle(DefaultQuery<I,Word<O>> ceQuery)	Performs a single refinement of the hypothesis, i.e., without repeated counterexample evaluation.
protected Word<O>	succEffect(Word<O> effect)

Methods inherited from class de.learnlib.algorithm.ttt.base.AbstractTTTLearner

addAlphabetSymbol, allNodesFinal, closeTransitions, createMap, createTransition, declareFinal, finalizeAny, findOutputInconsistency, getAnySuccessor, getAnySuccessor, getAnyTarget, getDeterministicState, getDiscriminationTree, getHypothesisDS, getNondetSuccessors, link, makeTree, query, query, refineHypothesis, resume, split, startLearning, suspend

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.learnlib.algorithm.LearningAlgorithm

refineHypothesis, startLearning

Constructor Detail

TTTLearnerMoore

public TTTLearnerMoore(Alphabet<I> alphabet,
                       MembershipOracle<I,Word<O>> oracle,
                       AcexAnalyzer analyzer)

Method Detail

succEffect

protected Word<O> succEffect(Word<O> effect)

Specified by:

succEffect in class AbstractTTTLearner<MooreMachine<?,I,?,O>,I,Word<O>>

predictSuccOutcome

protected Word<O> predictSuccOutcome(TTTTransition<I,Word<O>> trans,
                                     AbstractBaseDTNode<I,Word<O>> succSeparator)

Specified by:

predictSuccOutcome in class AbstractTTTLearner<MooreMachine<?,I,?,O>,I,Word<O>>

initializeState

protected void initializeState(TTTState<I,Word<O>> state)

Description copied from class: AbstractTTTLearner

Initializes a state. Creates its outgoing transition objects, and adds them to the "open" list.

Overrides:

initializeState in class AbstractTTTLearner<MooreMachine<?,I,?,O>,I,Word<O>>

Parameters:

state - the state to initialize

refineHypothesisSingle

protected boolean refineHypothesisSingle(DefaultQuery<I,Word<O>> ceQuery)

Description copied from class: AbstractTTTLearner

Performs a single refinement of the hypothesis, i.e., without repeated counterexample evaluation. The parameter and return value have the same significance as in AbstractTTTLearner.refineHypothesis(DefaultQuery).

Overrides:

refineHypothesisSingle in class AbstractTTTLearner<MooreMachine<?,I,?,O>,I,Word<O>>

Parameters:

ceQuery - the counterexample (query) to be used for refinement

Returns:

true if the hypothesis was refined, false otherwise

deriveAcex

protected OutInconsPrefixTransformAcex<I,Word<O>> deriveAcex(OutputInconsistency<I,Word<O>> outIncons)

Overrides:

deriveAcex in class AbstractTTTLearner<MooreMachine<?,I,?,O>,I,Word<O>>

computeHypothesisOutput

protected Word<O> computeHypothesisOutput(TTTState<I,Word<O>> state,
                                          Word<I> suffix)

Specified by:

computeHypothesisOutput in class AbstractTTTLearner<MooreMachine<?,I,?,O>,I,Word<O>>

createNewNode

protected AbstractBaseDTNode<I,Word<O>> createNewNode(AbstractBaseDTNode<I,Word<O>> parent,
                                                            Word<O> parentOutput)

Specified by:

createNewNode in class AbstractTTTLearner<MooreMachine<?,I,?,O>,I,Word<O>>

getHypothesisModel

public TTTHypothesisMoore<I,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().

Specified by:

getHypothesisModel in interface LearningAlgorithm<MooreMachine<?,I,?,O>,I,Word<O>>

Returns:

the current hypothesis model.