Package de.learnlib.testsupport.it.learner

Interface LearnerVariantList<M,I,D>

Type Parameters:

M - hypothesis model type (upper bound)

I - input symbol type

D - output type

All Known Subinterfaces:

LearnerVariantList.DFALearnerVariantList<I>, LearnerVariantList.MealyLearnerVariantList<I,O>, LearnerVariantList.MealySymLearnerVariantList<I,O>, LearnerVariantList.MooreLearnerVariantList<I,O>, LearnerVariantList.MooreSymLearnerVariantList<I,O>, LearnerVariantList.OneSEVPALearnerVariantList<I>, LearnerVariantList.SBALearnerVariantList<I>, LearnerVariantList.SPALearnerVariantList<I>, LearnerVariantList.SPMMLearnerVariantList<I,O>

All Known Implementing Classes:

LearnerVariantListImpl, LearnerVariantListImpl.DFALearnerVariantListImpl, LearnerVariantListImpl.MealyLearnerVariantListImpl, LearnerVariantListImpl.MealySymLearnerVariantListImpl, LearnerVariantListImpl.MooreLearnerVariantListImpl, LearnerVariantListImpl.MooreSymLearnerVariantListImpl, LearnerVariantListImpl.OneSEVPALearnerVariantListImpl, LearnerVariantListImpl.SBALearnerVariantListImpl, LearnerVariantListImpl.SPALearnerVariantListImpl, LearnerVariantListImpl.SPMMLearnerVariantListImpl

public interface LearnerVariantList<M,I,D>

A write-only list to store multiple variants of a learning algorithm.

Usually, there should be one integration test class per learning algorithm. However, in many cases a single learning algorithm can be configured in numerous ways, all (or many) of which should be tested independently. Due to the large number of possible combinations, it is undesirable to create a single integration test class for each configuration; instead, these variants should be configured and created programmatically. The purpose of the variant list is to offer a convenient interface for storing all these variants.

Nested Class Summary

Nested Classes

Modifier and Type	Interface	Description
static interface	LearnerVariantList.DFALearnerVariantList<I>
static interface	LearnerVariantList.MealyLearnerVariantList<I,O>
static interface	LearnerVariantList.MealySymLearnerVariantList<I,O>
static interface	LearnerVariantList.MooreLearnerVariantList<I,O>
static interface	LearnerVariantList.MooreSymLearnerVariantList<I,O>
static interface	LearnerVariantList.OneSEVPALearnerVariantList<I>
static interface	LearnerVariantList.SBALearnerVariantList<I>
static interface	LearnerVariantList.SPALearnerVariantList<I>
static interface	LearnerVariantList.SPMMLearnerVariantList<I,O>

Method Summary

Modifier and Type	Method	Description
void	addLearnerVariant(String name, LearningAlgorithm<? extends M,I,D> learner)	Adds a learner variant with the default maximum number of rounds (i.e., the size of the target automaton) to the list.
void	addLearnerVariant(String name, LearningAlgorithm<? extends M,I,D> learner, int maxRounds)	Adds a learner variant with a given maximum number of rounds to the list.

Method Detail

addLearnerVariant

void addLearnerVariant(String name,
                       LearningAlgorithm<? extends M,I,D> learner)

Adds a learner variant with the default maximum number of rounds (i.e., the size of the target automaton) to the list.

This is a convenience method, equivalent to invoking addLearnerVariant(name, learner, -1).

Parameters:

name - the name of the variant

learner - the algorithm instance for this variant

addLearnerVariant

void addLearnerVariant(String name,
                       LearningAlgorithm<? extends M,I,D> learner,
                       int maxRounds)

Adds a learner variant with a given maximum number of rounds to the list.

Parameters:

name - the name of the variant

learner - the algorithm instance for this variant

maxRounds - the maximum number of rounds for the specified target automaton. If a value less than or equal to zero is specified, the default maximum number of rounds (the size of the target automaton) is assumed.