Package net.sf.tweety.logics.mln.reasoner

Class ApproximateNaiveMlnReasoner

java.lang.Object

net.sf.tweety.logics.mln.reasoner.AbstractMlnReasoner

net.sf.tweety.logics.mln.reasoner.ApproximateNaiveMlnReasoner

All Implemented Interfaces:

net.sf.tweety.commons.QuantitativeReasoner<MarkovLogicNetwork,net.sf.tweety.logics.fol.syntax.FolFormula>, net.sf.tweety.commons.Reasoner<Double,MarkovLogicNetwork,net.sf.tweety.logics.fol.syntax.FolFormula>

public class ApproximateNaiveMlnReasoner
extends AbstractMlnReasoner

This reasoner performs approximate reasoning with MLNs by considering only a subset of all Herbrand interpretations. This subset is chosen by first randomly selecting a set of Herbrand interpretations and then selecting the subset of this set with maximum weights.

Author:

Matthias Thimm

Constructor Summary

Constructors

Constructor	Description
ApproximateNaiveMlnReasoner(long maxNumberOfSelectedInterpretations, long maxNumberOfInterpretationsForModel)	Creates a new ApproximateNaiveMlnReasoner.

Method Summary

Modifier and Type	Method	Description
Map<net.sf.tweety.logics.fol.semantics.HerbrandInterpretation,Double>	computeModel(MarkovLogicNetwork mln, net.sf.tweety.logics.fol.syntax.FolSignature signature)	Computes the model of the given MLN wrt.
protected double	doQuery(MarkovLogicNetwork mln, net.sf.tweety.logics.fol.syntax.FolFormula query, net.sf.tweety.logics.fol.syntax.FolSignature signature)	Performs the actual querying.

Methods inherited from class net.sf.tweety.logics.mln.reasoner.AbstractMlnReasoner

computeWeight, numberOfGroundSatisfactions, query, query

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ApproximateNaiveMlnReasoner

public ApproximateNaiveMlnReasoner(long maxNumberOfSelectedInterpretations,
                                   long maxNumberOfInterpretationsForModel)

Creates a new ApproximateNaiveMlnReasoner.

Parameters:

maxNumberOfSelectedInterpretations - the maximum number of interpretations selected from the whole set of interpretations. Is -1 if all interpretations are to be selected.

maxNumberOfInterpretationsForModel - the maximum number of interpretations used for the model. Those interpretations are the subset of the interpretations selected with maximum weight. Is -1 if all interpretations are used for the model. It has to be maxNumberOfSelectedInterpretations >= maxNumberOfInterpretationsForModel.

Method Detail

doQuery

protected double doQuery(MarkovLogicNetwork mln,
                         net.sf.tweety.logics.fol.syntax.FolFormula query,
                         net.sf.tweety.logics.fol.syntax.FolSignature signature)

Description copied from class: AbstractMlnReasoner

Performs the actual querying.

Specified by:

doQuery in class AbstractMlnReasoner

Parameters:

mln - an MLN

query - a fol formula guaranteed to be ground.

signature - the signature

Returns:

the answer of the query.

computeModel

public Map<net.sf.tweety.logics.fol.semantics.HerbrandInterpretation,Double> computeModel(MarkovLogicNetwork mln,
                                                                                                net.sf.tweety.logics.fol.syntax.FolSignature signature)

Computes the model of the given MLN wrt. the optimization parameters

Parameters:

mln - some mln

signature - some signature

Returns:

the model of the given MLN wrt. the optimization parameters.