de.learnlib.algorithms.rpni

Class BlueFringeEDSMDFA<I>

java.lang.Object

de.learnlib.algorithms.rpni.AbstractBlueFringeRPNI<I,Boolean,Boolean,Void,net.automatalib.automata.fsa.DFA<?,I>>

de.learnlib.algorithms.rpni.BlueFringeRPNIDFA<I>

de.learnlib.algorithms.rpni.BlueFringeEDSMDFA<I>

Type Parameters:

I - input symbol type

All Implemented Interfaces:

PassiveLearningAlgorithm<net.automatalib.automata.fsa.DFA<?,I>,I,Boolean>, PassiveLearningAlgorithm.PassiveAcceptorLearner<net.automatalib.automata.fsa.DFA<?,I>,I>, PassiveLearningAlgorithm.PassiveDFALearner<I>

public class BlueFringeEDSMDFA<I>
extends BlueFringeRPNIDFA<I>

A state-merging learning algorithm based on the evidence principle. On an operational level this algorithm is very similar to the BlueFringeRPNIDFA algorithm. However, whereas the basic RPNI approach merges the very first pair of nodes that resemble a valid merge, the EDSM variant prioritizes the promotion of states (to be unmergable) and only proceeds to merge states, if there exists at least one mergable blue state for every red state. If such a situation occurs, the algorithm merges the two states whose merge would yield the biggest score (see EDSMUtil.score(UniversalDeterministicAutomaton, List, List)). Thus the behavior of this algorithm is more passive, or as the name suggest evidence-driven.

Author:

frohme

Nested Class Summary

Nested classes/interfaces inherited from interface de.learnlib.api.algorithm.PassiveLearningAlgorithm

PassiveLearningAlgorithm.PassiveAcceptorLearner<M extends net.automatalib.automata.fsa.FiniteStateAcceptor<?,I>,I>, PassiveLearningAlgorithm.PassiveDFALearner<I>, PassiveLearningAlgorithm.PassiveMealyLearner<I,O>, PassiveLearningAlgorithm.PassiveNFALearner<I>

Field Summary

Fields inherited from class de.learnlib.algorithms.rpni.BlueFringeRPNIDFA

negative, positive

Fields inherited from class de.learnlib.algorithms.rpni.AbstractBlueFringeRPNI

alphabet, alphabetSize, deterministic, order, parallel

Constructor Summary

Constructors

Constructor and Description
BlueFringeEDSMDFA(net.automatalib.words.Alphabet<I> alphabet) Constructor.

Method Summary

Modifier and Type	Method and Description
net.automatalib.automata.fsa.DFA<?,I>	computeModel()

Methods inherited from class de.learnlib.algorithms.rpni.BlueFringeRPNIDFA

addSamples, initializePTA, ptaToModel

Methods inherited from class de.learnlib.algorithms.rpni.AbstractBlueFringeRPNI

decideOnValidMerge, setDeterministic, setParallel, tryMerge

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.learnlib.api.algorithm.PassiveLearningAlgorithm.PassiveAcceptorLearner

addNegativeSample, addNegativeSamples, addNegativeSamples, addPositiveSample, addPositiveSamples, addPositiveSamples

Methods inherited from interface de.learnlib.api.algorithm.PassiveLearningAlgorithm

addSample, addSample, addSamples, addSamples, addSamples

Constructor Detail

BlueFringeEDSMDFA

public BlueFringeEDSMDFA(net.automatalib.words.Alphabet<I> alphabet)

Constructor.

Parameters:

alphabet - the alphabet

Method Detail

computeModel

public net.automatalib.automata.fsa.DFA<?,I> computeModel()

Specified by:

computeModel in interface PassiveLearningAlgorithm<net.automatalib.automata.fsa.DFA<?,I>,I,Boolean>

Overrides:

computeModel in class AbstractBlueFringeRPNI<I,Boolean,Boolean,Void,net.automatalib.automata.fsa.DFA<?,I>>