Package org.tweetyproject.logics.pcl.analysis
package org.tweetyproject.logics.pcl.analysis

ClassDescriptionThe common ancestor vor creeping machine shops, see [Diss, Thimm] for details.This class implements a consistency restorer using balanced distance minimization, see [Diss, Thimm] for details.This consistency restorer determines the new probabilities of conditionals by computing the MEdistribution of each maximal consistent subset of the knowledge base, then convex combining those yielding a distribution P, and extracting the new probabilities from P.This consistency restorer determines the new probabilities of conditionals by computing the MEdistribution of each single conditional, then convex combining those yielding a distribution P, and extracting the new probabilities from P.This class models the distance minimization inconsistency measure as proposed in [Thimm,UAI,2009], extended by the use of different pnorms.This consistency restorer uses the distance minimization inconsistency measure to restore consistency.Uses the generalized MEmodel of a knowledge base to repair it, cf.This class models an approximation from below to the distance minimization inconsistency measure as proposed in [Thimm,UAI,2009], see [PhD thesis, Thimm].This consistency restorer uses the idea of the upper approximative distance minimization inconsistency measure to compute a MEprobability distribution and adjust the probabilities of the conditionals accordingly.This class implements the mean distance culpability measure, see [PhD thesis, Thimm].This class models the minimal violation inconsistency measure for the 2norm.Repairs a probabilistic belief base by taking the probabilities from the probability function that minimizes the "minimal violation inconsistency measure" with respect to the euclidean norm.Repairs a probabilistic belief base by taking the probabilities from the probability function that minimizes the "minimal violation inconsistency measure" with respect to the euclidean norm.Repairs a probabilistic belief base by taking the probabilities from the probability function that minimizes the "minimal violation inconsistency measure" with respect to the euclidean norm.This class provides a general implementation for the minimal violation inconsistency measure, cf.This approach to consistency restoration follows the approach proposed in [Thimm, DKB, 2011].Repairs a probabilistic belief base by taking the probabilities from the probability function that minimizes the "minimum violation inconsistency measure".This class models the normalized distance minimization inconsistency measure, see [PhD thesis, Thimm].This class models a normalized approximation from below to the distance minimization inconsistency measure as proposed in [Thimm,UAI,2009], see [PhD thesis, Thimm].This class models a normalized approximation from above to the distance minimization inconsistency measure as proposed in [Thimm,UAI,2009], see [PhD thesis, Thimm].This class is capable of restoring consistency of a possible inconsistent probabilistic conditional belief set.This class is capable of checking whether a given conditional knowledge base is consistent by searching for the root of some equivalent multidimensional function.This class is capable of restoring consistency of a possible inconsistent probabilistic conditional belief set.Classes implementing this interface represent signed culpability measures, i.e.This class is capable of restoring consistency of a possible inconsistent probabilistic conditional belief set.This class is capable of restoring consistency of a possible inconsistent probabilistic conditional belief set.This class models an approximation from above to the distance minimization inconsistency measure as proposed in [Thimm,UAI,2009], see [PhD thesis, Thimm].