Package org.tweetyproject.arg.dung.reasoner

Class SimplePreferredReasoner

java.lang.Object

org.tweetyproject.arg.dung.reasoner.AbstractDungReasoner

org.tweetyproject.arg.dung.reasoner.AbstractExtensionReasoner

org.tweetyproject.arg.dung.reasoner.SimplePreferredReasoner

All Implemented Interfaces:

ModelProvider<Argument,DungTheory,Extension<DungTheory>>, PostulateEvaluatable<Argument>, QualitativeReasoner<DungTheory,Argument>, Reasoner<Boolean,DungTheory,Argument>

public class SimplePreferredReasoner
extends AbstractExtensionReasoner

This reasoner for Dung theories performs inference on the preferred extensions. Computes the set of all preferred extensions, i.e., all maximal admissable sets. It does so by first computing all complete extensions and then check for set maximality.

Author:

Matthias Thimm

Constructor Summary

Constructors

Constructor	Description
SimplePreferredReasoner()

Method Summary

Modifier and Type	Method	Description
Extension<DungTheory>	getModel(DungTheory bbase)	Returns a single (dedicated) model of the given belief base.
Collection<Extension<DungTheory>>	getModels(DungTheory bbase)	Returns a characterizing model of the given belief base

Methods inherited from class org.tweetyproject.arg.dung.reasoner.AbstractExtensionReasoner

getSimpleReasonerForSemantics, isInstalled, query, query

Methods inherited from class java.lang.Object

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

Constructor Details

SimplePreferredReasoner

public SimplePreferredReasoner()

Method Details

getModels

public Collection<Extension<DungTheory>> getModels(DungTheory bbase)

Description copied from interface: ModelProvider

Returns a characterizing model of the given belief base

Parameters:

bbase - some belief base

Returns:

the (selected) models of the belief base

getModel

public Extension<DungTheory> getModel(DungTheory bbase)

Description copied from interface: ModelProvider

Returns a single (dedicated) model of the given belief base. If the implemented method allows for more than one dedicated model, the selection may be non-deterministic.

Parameters:

bbase - some belief base

Returns:

a selected model of the belief base.