Class TTTLearnerMoore<I,​O>

    • Constructor Detail

      • TTTLearnerMoore

        public TTTLearnerMoore​(net.automatalib.alphabet.Alphabet<I> alphabet,
                               MembershipOracle<I,​net.automatalib.word.Word<O>> oracle,
                               AcexAnalyzer analyzer)
    • Method Detail

      • succEffect

        protected net.automatalib.word.Word<O> succEffect​(net.automatalib.word.Word<O> effect)
        Specified by:
        succEffect in class AbstractTTTLearner<net.automatalib.automaton.transducer.MooreMachine<?,​I,​?,​O>,​I,​net.automatalib.word.Word<O>>
      • initializeState

        protected void initializeState​(TTTState<I,​net.automatalib.word.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<net.automatalib.automaton.transducer.MooreMachine<?,​I,​?,​O>,​I,​net.automatalib.word.Word<O>>
        Parameters:
        state - the state to initialize
      • refineHypothesisSingle

        protected boolean refineHypothesisSingle​(DefaultQuery<I,​net.automatalib.word.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<net.automatalib.automaton.transducer.MooreMachine<?,​I,​?,​O>,​I,​net.automatalib.word.Word<O>>
        Parameters:
        ceQuery - the counterexample (query) to be used for refinement
        Returns:
        true if the hypothesis was refined, false otherwise
      • computeHypothesisOutput

        protected net.automatalib.word.Word<O> computeHypothesisOutput​(TTTState<I,​net.automatalib.word.Word<O>> state,
                                                                       net.automatalib.word.Word<I> suffix)
        Specified by:
        computeHypothesisOutput in class AbstractTTTLearner<net.automatalib.automaton.transducer.MooreMachine<?,​I,​?,​O>,​I,​net.automatalib.word.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 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().

        Specified by:
        getHypothesisModel in interface LearningAlgorithm<net.automatalib.automaton.transducer.MooreMachine<?,​I,​?,​O>,​I,​net.automatalib.word.Word<O>>
        Returns:
        the current hypothesis model.