Package org.tweetyproject.logics.mln.reasoner

Class ApproximateNaiveMlnReasoner

java.lang.Object
org.tweetyproject.logics.mln.reasoner.AbstractMlnReasoner
org.tweetyproject.logics.mln.reasoner.ApproximateNaiveMlnReasoner
All Implemented Interfaces:
QuantitativeReasoner<MarkovLogicNetwork,FolFormula>, Reasoner<Double,MarkovLogicNetwork,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 Details

    • 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 Details

    • computeModel

      public Map<HerbrandInterpretation,Double> computeModel(MarkovLogicNetwork mln, 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.

    • isInstalled

      public boolean isInstalled()
      Returns:
      if reasoner is installed