Class MTRankingReasoner
- java.lang.Object
-
- net.sf.tweety.arg.rankings.reasoner.AbstractRankingReasoner<NumericalArgumentRanking>
-
- net.sf.tweety.arg.rankings.reasoner.MTRankingReasoner
-
- All Implemented Interfaces:
ModelProvider<Argument,DungTheory,NumericalArgumentRanking>
,PostulateEvaluatable<Argument>
public class MTRankingReasoner extends AbstractRankingReasoner<NumericalArgumentRanking>
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 MTRankingReasoner()
-
Method Summary
Modifier and Type Method Description double
computeDegreeOfAcceptability(java.util.Collection<Argument> A, java.util.Collection<Argument> B, DungTheory kb)
Computes the degree of acceptability of the strategy A wrt.double
computeRewards(java.util.Collection<Argument> A, java.util.Collection<Argument> B, DungTheory kb)
Computes the rewards of the given strategy (set of arguments).double
computeStrengthOfArgument(Argument a, DungTheory kb, java.util.Set<java.util.Set<Argument>> subsets)
Computes the value of the zero-sum game for the given argument.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
-
-
-
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.
-
computeStrengthOfArgument
public double computeStrengthOfArgument(Argument a, DungTheory kb, java.util.Set<java.util.Set<Argument>> subsets)
Computes the value of the zero-sum game for the given argument.- Parameters:
a
- an Argumentkb
- DungTheorysubsets
- all subsets of the knowledge base- Returns:
- strength value of the given argument
-
computeRewards
public double computeRewards(java.util.Collection<Argument> A, java.util.Collection<Argument> B, DungTheory kb)
Computes the rewards of the given strategy (set of arguments).- Parameters:
A
- set of argumentsB
- set of argumentskb
- knowledge base containing the relations between A and B- Returns:
- rewards of A
-
computeDegreeOfAcceptability
public double computeDegreeOfAcceptability(java.util.Collection<Argument> A, java.util.Collection<Argument> B, DungTheory kb)
Computes the degree of acceptability of the strategy A wrt. strategy B.- Parameters:
A
- set of argumentsB
- set of argumentskb
- knowledge base containing the relations between A and B- Returns:
- degree of acceptability of A wrt. B.
-
-