Class ProbabilisticRankingReasoner
java.lang.Object
org.tweetyproject.arg.rankings.reasoner.AbstractRankingReasoner<NumericalPartialOrder<Argument,DungTheory>>
org.tweetyproject.arg.rankings.reasoner.ProbabilisticRankingReasoner
- All Implemented Interfaces:
ModelProvider<Argument,
,DungTheory, NumericalPartialOrder<Argument, DungTheory>> PostulateEvaluatable<Argument>
public class ProbabilisticRankingReasoner
extends AbstractRankingReasoner<NumericalPartialOrder<Argument,DungTheory>>
Implements a graded semantics reasoner based on the ideas from
[Thimm, Cerutti, Rienstra. Probabilistic Graded Semantics. COMMA 2018].
- Author:
- Matthias Thimm
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Field Summary
Modifier and TypeFieldDescriptionstatic int
Number of trials for the used monte carlo search (this is a factor multiplied with the number of arguments of the actual framework) -
Constructor Summary
ConstructorDescriptionProbabilisticRankingReasoner
(Semantics sem, Probability p, boolean exactInference) Creates a new ProbabilisticRankingReasoner. -
Method Summary
Modifier and TypeMethodDescriptiongetModel
(DungTheory aaf) Returns a single (dedicated) model of the given belief base.getModels
(DungTheory bbase) Returns a characterizing model of the given belief baseboolean
natively installed
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Field Details
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NUMBER_OF_TRIALS
public static int NUMBER_OF_TRIALSNumber of trials for the used monte carlo search (this is a factor multiplied with the number of arguments of the actual framework)
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Constructor Details
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ProbabilisticRankingReasoner
Creates a new ProbabilisticRankingReasoner.- Parameters:
sem
- The classical semantics used for evaluating subgraphsp
- The probability used for all arguments to instantiate a probabilistic argumentation frameworkexactInference
- Whether to use exact inference.
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Method Details
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getModels
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
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:
aaf
- some belief base- Returns:
- a selected model of the belief base.
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isInstalled
public boolean isInstalled()natively installed- Specified by:
isInstalled
in classAbstractRankingReasoner<NumericalPartialOrder<Argument,
DungTheory>>
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