Package org.tweetyproject.arg.rankings.reasoner

Class StrategyBasedRankingReasoner

java.lang.Object

org.tweetyproject.arg.rankings.reasoner.AbstractRankingReasoner<NumericalPartialOrder<Argument,DungTheory>>

org.tweetyproject.arg.rankings.reasoner.StrategyBasedRankingReasoner

All Implemented Interfaces:

ModelProvider<Argument,DungTheory,NumericalPartialOrder<Argument,DungTheory>>, PostulateEvaluatable<Argument>

public class StrategyBasedRankingReasoner
extends AbstractRankingReasoner<NumericalPartialOrder<Argument,DungTheory>>

This class implements the argument ranking approach of [Matt, Toni. A game-theoretic measure of argument strength for abstract argumentation. JELIA 2008]. In this approach, the strength of an argument is computed using a two-person zero-sum strategic game in which the strategies of players are sets of arguments.

Author:

Anna Gessler

Constructor Summary

Constructors

Constructor	Description
StrategyBasedRankingReasoner()	Default Constructor

Method Summary

Modifier and Type	Method	Description
double	computeDegreeOfAcceptability(Collection<Argument> A, Collection<Argument> B, DungTheory kb)	Computes the degree of acceptability of the strategy A wrt.
double	computeRewards(Collection<Argument> A, Collection<Argument> B, DungTheory kb)	Computes the rewards of the given strategy (set of arguments).
double	computeStrengthOfArgument(Argument a, DungTheory kb, Set<Set<Argument>> subsets)	Computes the value of the zero-sum game for the given argument.
NumericalPartialOrder<Argument,DungTheory>	getModel(DungTheory kb)	Returns a single (dedicated) model of the given belief base.
Collection<NumericalPartialOrder<Argument,DungTheory>>	getModels(DungTheory bbase)	Returns a characterizing model of the given belief base
boolean	isInstalled()	natively installed

Methods inherited from class java.lang.Object

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

Constructor Details

StrategyBasedRankingReasoner

public StrategyBasedRankingReasoner()

Default Constructor

Method Details

getModels

public Collection<NumericalPartialOrder<Argument,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 NumericalPartialOrder<Argument,DungTheory> 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.

computeStrengthOfArgument

public double computeStrengthOfArgument(Argument a,
 DungTheory kb,
 Set<Set<Argument>> subsets)

Computes the value of the zero-sum game for the given argument.

Parameters:

a - an Argument

kb - DungTheory

subsets - all subsets of the knowledge base

Returns:

strength value of the given argument

computeRewards

public double computeRewards(Collection<Argument> A,
 Collection<Argument> B,
 DungTheory kb)

Computes the rewards of the given strategy (set of arguments).

Parameters:

A - set of arguments

B - set of arguments

kb - knowledge base containing the relations between A and B

Returns:

rewards of A

computeDegreeOfAcceptability

public double computeDegreeOfAcceptability(Collection<Argument> A,
 Collection<Argument> B,
 DungTheory kb)

Computes the degree of acceptability of the strategy A wrt. strategy B.

Parameters:

A - set of arguments

B - set of arguments

kb - knowledge base containing the relations between A and B

Returns:

degree of acceptability of A wrt. B.

isInstalled

public boolean isInstalled()

natively installed

Specified by:

isInstalled in class AbstractRankingReasoner<NumericalPartialOrder<Argument,DungTheory>>

Returns:

is installed status