Class SimpleSamplingMlnReasoner
- java.lang.Object
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- net.sf.tweety.logics.mln.reasoner.AbstractMlnReasoner
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- net.sf.tweety.logics.mln.reasoner.SimpleSamplingMlnReasoner
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- All Implemented Interfaces:
QuantitativeReasoner<MarkovLogicNetwork,FolFormula>
,Reasoner<java.lang.Double,MarkovLogicNetwork,FolFormula>
public class SimpleSamplingMlnReasoner extends AbstractMlnReasoner
This MLN reasoner employs simple random sampling from the set of interpretations to compute the probability of a formula.- Author:
- Matthias Thimm
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Field Summary
Fields Modifier and Type Field Description private int
numOfPositiveTests
private double
precision
The computation is aborted when the given precision is reached for at least numOfPositive number of consecutive tests.
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Constructor Summary
Constructors Constructor Description SimpleSamplingMlnReasoner(double precision, int numOfPositiveTests)
Creates a new SimpleSamplingMlnReasoner for the given Markov logic network.
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Method Summary
Modifier and Type Method Description protected double
doQuery(MarkovLogicNetwork mln, FolFormula query, FolSignature signature)
Performs the actual querying.-
Methods inherited from class net.sf.tweety.logics.mln.reasoner.AbstractMlnReasoner
computeWeight, numberOfGroundSatisfactions, query, query
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Constructor Detail
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SimpleSamplingMlnReasoner
public SimpleSamplingMlnReasoner(double precision, int numOfPositiveTests)
Creates a new SimpleSamplingMlnReasoner for the given Markov logic network.- Parameters:
precision
- the precisionnumOfPositiveTests
- the number of positive consecutive tests on precision
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Method Detail
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doQuery
protected double doQuery(MarkovLogicNetwork mln, FolFormula query, FolSignature signature)
Description copied from class:AbstractMlnReasoner
Performs the actual querying.- Specified by:
doQuery
in classAbstractMlnReasoner
- Parameters:
mln
- an MLNquery
- a fol formula guaranteed to be ground.signature
- the signature- Returns:
- the answer of the query.
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