Package net.sf.tweety.arg.rankings.reasoner

Class SAFRankingReasoner

java.lang.Object

net.sf.tweety.arg.rankings.reasoner.AbstractRankingReasoner<NumericalArgumentRanking>

net.sf.tweety.arg.rankings.reasoner.SAFRankingReasoner

All Implemented Interfaces:

ModelProvider<Argument,DungTheory,NumericalArgumentRanking>, PostulateEvaluatable<Argument>

public class SAFRankingReasoner
extends AbstractRankingReasoner<NumericalArgumentRanking>

This class implements the ranking-based "SAF" semantics approach as proposed by [Bonzon, Delobelle, Konieczny, Maudet. A Comparative Study of Ranking-Based Semantics for Abstract Argumentation. AAAI 2016]. It uses social abstract argumentation frameworks and the simple product semantic which were introduced by [Leite, Martins. Social abstract argumentation. IJCAI 2011].

Author:

Anna Gessler

Constructor Summary

Constructors

Constructor	Description
SAFRankingReasoner()	Create a new SAFRankingReasoner with default parameters.
SAFRankingReasoner(double epsilon)	Create a new SAFRankingReasoner with the given epsilon for the SimpleProductSemantic.
SAFRankingReasoner(double epsilon, double tolerance)	Create a new SAFRankingReasoner with the given epsilon and the given tolerance for the SimpleProductSemantic.
SAFRankingReasoner(double epsilon, double precision, double tolerance)	Create a new SAFRankingReasoner with the given epsilon, the given precision and the given tolerance for the SimpleProductSemantic.

Method Summary

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

Methods inherited from class java.lang.Object

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

Constructor Detail

SAFRankingReasoner

public SAFRankingReasoner()

Create a new SAFRankingReasoner with default parameters.

SAFRankingReasoner

public SAFRankingReasoner(double epsilon)

Create a new SAFRankingReasoner with the given epsilon for the SimpleProductSemantic.

Parameters:

epsilon - must be non-negative

SAFRankingReasoner

public SAFRankingReasoner(double epsilon,
                          double tolerance)

Create a new SAFRankingReasoner with the given epsilon and the given tolerance for the SimpleProductSemantic.

Parameters:

epsilon - TODO add description

tolerance - TODO add description

SAFRankingReasoner

public SAFRankingReasoner(double epsilon,
                          double precision,
                          double tolerance)

Create a new SAFRankingReasoner with the given epsilon, the given precision and the given tolerance for the SimpleProductSemantic.

Parameters:

epsilon - TODO add description

precision - TODO add description

tolerance - TODO add description

Method Detail

getModels

public java.util.Collection<NumericalArgumentRanking> 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 NumericalArgumentRanking getModel(DungTheory kb)

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:

kb - some belief base

Returns:

a selected model of the belief base.