Package net.sf.tweety.arg.prob.semantics
Class ProbabilisticExtension
- java.lang.Object
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- net.sf.tweety.math.probability.ProbabilityFunction<Extension>
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- net.sf.tweety.arg.prob.semantics.ProbabilisticExtension
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- All Implemented Interfaces:
java.util.Map<Extension,Probability>
public class ProbabilisticExtension extends ProbabilityFunction<Extension>
This class implements a probabilistic interpretation for Dung argumentation frameworks, cf. [Thimm:2012].- Author:
- Matthias Thimm
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Constructor Summary
Constructors Constructor Description ProbabilisticExtension()
Creates a new probabilistic extension for the given theory.
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Method Summary
Modifier and Type Method Description Extension
geLowerCut(DungTheory theory, double delta)
Returns the lower cut of this probabilistic extension wrt.Extension
getAllArguments()
Returns the set of all arguments appearing.static ProbabilisticExtension
getCharacteristicProbabilisticExtension(DungTheory theory, AbstractArgumentationInterpretation i)
Returns the characteristic probabilistic extension of the given interpretation, i.e.Labeling
getEpistemicLabeling()
Returns the epistemic labeling of this probabilistic extension, i.e.Extension
getUpperCut(DungTheory theory, double delta)
Returns the upper cut of this probabilistic extension wrt.boolean
isCongruent(Labeling l)
Checks whether the given labeling is congruent to this probabilistic extension, i.e.Probability
probability(Argument a)
Computes the probability of the given argument.-
Methods inherited from class net.sf.tweety.math.probability.ProbabilityFunction
clear, containsKey, containsValue, convexCombination, convexCombination, entrySet, equals, get, getProbabilityVector, getProbabilityVectorAsDoubles, getUniformDistribution, hashCode, isEmpty, isNormalized, keySet, linearCombination, normalize, probability, probability, put, putAll, remove, sample, sample, size, toString, values
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Method Detail
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probability
public Probability probability(Argument a)
Computes the probability of the given argument.- Parameters:
a
- some argument- Returns:
- the probability of the argument.
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getAllArguments
public Extension getAllArguments()
Returns the set of all arguments appearing.- Returns:
- the set of all arguments appearing.
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getUpperCut
public Extension getUpperCut(DungTheory theory, double delta)
Returns the upper cut of this probabilistic extension wrt. delta, i.e. all arguments that have probability >= delta.- Parameters:
theory
- a Dung theory.delta
- some threshold.- Returns:
- the set of arguments that have probability >= delta.
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geLowerCut
public Extension geLowerCut(DungTheory theory, double delta)
Returns the lower cut of this probabilistic extension wrt. delta, i.e. all arguments that have probability <= delta.- Parameters:
theory
- a Dung theory.delta
- some threshold.- Returns:
- the set of arguments that have probability <= delta.
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isCongruent
public boolean isCongruent(Labeling l)
Checks whether the given labeling is congruent to this probabilistic extension, i.e. whether l(A)=in <=> P(A)=1, l(A)=out <=> P(A)=0, l(A)=undec <=> P(A)=0.5- Parameters:
l
- some labelling- Returns:
- true iff the given labeling is congruent to this probabilistic extension
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getEpistemicLabeling
public Labeling getEpistemicLabeling()
Returns the epistemic labeling of this probabilistic extension, i.e. the labeling with l(A)=in if P(A)>0.5, l(A)=undecided if P(A)=0.5, and l(A)=0 if P(A)=0.- Returns:
- the epistemic labeling of this probabilistic extension
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getCharacteristicProbabilisticExtension
public static ProbabilisticExtension getCharacteristicProbabilisticExtension(DungTheory theory, AbstractArgumentationInterpretation i)
Returns the characteristic probabilistic extension of the given interpretation, i.e. the probabilistic extension that assigns probability 0.5 to the given in arguments of the labeling and 0.5 to the union of the in and undecided arguments- Parameters:
theory
- some Dung theoryi
- some argumentation interpretation- Returns:
- the characteristic probabilistic extension of the given interpretation.
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