Class CategorizerRankingReasoner
- java.lang.Object
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- net.sf.tweety.arg.rankings.reasoner.AbstractRankingReasoner<NumericalArgumentRanking>
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- net.sf.tweety.arg.rankings.reasoner.CategorizerRankingReasoner
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- All Implemented Interfaces:
ModelProvider<Argument,DungTheory,NumericalArgumentRanking>
,PostulateEvaluatable<Argument>
public class CategorizerRankingReasoner extends AbstractRankingReasoner<NumericalArgumentRanking>
This class implements the "h-categorizer" argument ranking approach that was originally proposed by [Besnard, Hunter. A logic-based theory of deductive arguments. 2001] for deductive logics. It uses the Fixed-point algorithm of [Pu, Zhang, Luo, Luo. Argument Ranking with Categoriser Function. KSEM 2014] which allows for cycles in argumentation graphs.- Author:
- Anna Gessler
- See Also:
HCategorizer
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Constructor Summary
Constructors Constructor Description CategorizerRankingReasoner()
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Method Summary
Modifier and Type Method Description private double
calculateCategorizerFunction(double[] v_old, Matrix directAttackMatrix, int i)
Computes the h-Categorizer function.private double
getDistance(double[] v_old, double[] v)
Computes the Euclidean distance between to the given arrays.NumericalArgumentRanking
getModel(DungTheory base)
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
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Method Detail
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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
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getModel
public NumericalArgumentRanking getModel(DungTheory base)
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:
base
- some belief base- Returns:
- a selected model of the belief base.
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calculateCategorizerFunction
private double calculateCategorizerFunction(double[] v_old, Matrix directAttackMatrix, int i)
Computes the h-Categorizer function.- Parameters:
v_old
- array of double valuations that were computed in the previous iterationdirectAttackMatrix
- complete matrix of direct attacksi
- row of the attack matrix that will be used in the calculation- Returns:
- categorizer valuation
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getDistance
private double getDistance(double[] v_old, double[] v)
Computes the Euclidean distance between to the given arrays.- Parameters:
v_old
- first arrayv
- second array- Returns:
- distance between v and v_old
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