Uses of Class
org.tweetyproject.logics.pcl.syntax.PclBeliefSet

Packages that use PclBeliefSet

Package	Description
org.tweetyproject.logics.pcl.analysis
org.tweetyproject.logics.pcl.parser
org.tweetyproject.logics.pcl.reasoner
org.tweetyproject.logics.pcl.semantics
org.tweetyproject.logics.pcl.util

Uses of PclBeliefSet in org.tweetyproject.logics.pcl.analysis

Methods in org.tweetyproject.logics.pcl.analysis with parameters of type PclBeliefSet

Modifier and Type	Method	Description
Double	MeanDistanceCulpabilityMeasure.culpabilityMeasure(PclBeliefSet beliefSet, ProbabilisticConditional conditional)
Double	SignedCulpabilityMeasure.culpabilityMeasure(PclBeliefSet beliefSet, ProbabilisticConditional conditional)
Double	DistanceMinimizationInconsistencyMeasure.getDeviation(PclBeliefSet beliefSet, ProbabilisticConditional pc)	Returns the deviation of the given conditional in the nearest consistent belief set.
Double	MeanDistanceCulpabilityMeasure.sign(PclBeliefSet beliefSet, ProbabilisticConditional conditional)
Double	SignedCulpabilityMeasure.sign(PclBeliefSet beliefSet, ProbabilisticConditional conditional)	Determines the sign of the culpability of the given conditional in the given belief set, i.e.

Constructor parameters in org.tweetyproject.logics.pcl.analysis with type arguments of type PclBeliefSet

Modifier	Constructor	Description
	BalancedMachineShop(CulpabilityMeasure<ProbabilisticConditional,PclBeliefSet> culpabilityMeasure)
	PclBeliefSetQuadraticErrorMinimizationMachineShop(CulpabilityMeasure<ProbabilisticConditional,PclBeliefSet> culpabilityMeasure, OptimizationRootFinder rootFinder)	Creates a new machine shop based on the given culpability measure.
	SmoothedPenalizingCreepingMachineShop(OptimizationRootFinder rootFinder, CulpabilityMeasure<ProbabilisticConditional,PclBeliefSet> culpabilityMeasure)	Creates a new creeping machine shop based on the given culpability measure.

Uses of PclBeliefSet in org.tweetyproject.logics.pcl.parser

Methods in org.tweetyproject.logics.pcl.parser that return PclBeliefSet

Modifier and Type	Method	Description
PclBeliefSet	PclParser.parseBeliefBase(Reader reader)

Uses of PclBeliefSet in org.tweetyproject.logics.pcl.reasoner

Methods in org.tweetyproject.logics.pcl.reasoner with parameters of type PclBeliefSet

Modifier and Type	Method	Description
abstract ProbabilityDistribution<PossibleWorld>	AbstractPclReasoner.getModel(PclBeliefSet beliefbase)
ProbabilityDistribution<PossibleWorld>	DefaultMeReasoner.getModel(PclBeliefSet beliefbase)
ProbabilityDistribution<PossibleWorld>	DefaultMeReasoner.getModel(PclBeliefSet bs, PlSignature signature)	Computes the ME-distribution this reasoner bases on.
ProbabilityDistribution<PossibleWorld>	GeneralizedMeReasoner.getModel(PclBeliefSet beliefbase)
ProbabilityDistribution<PossibleWorld>	GeneralizedMeReasoner.getModel(PclBeliefSet bs, PlSignature signature)	Computes the ME-distribution this reasoner bases on.
abstract Collection<ProbabilityDistribution<PossibleWorld>>	AbstractPclReasoner.getModels(PclBeliefSet bbase)
Collection<ProbabilityDistribution<PossibleWorld>>	DefaultMeReasoner.getModels(PclBeliefSet bbase)
Collection<ProbabilityDistribution<PossibleWorld>>	GeneralizedMeReasoner.getModels(PclBeliefSet bbase)
abstract Double	AbstractPclReasoner.query(PclBeliefSet beliefbase, PlFormula formula)
Double	DefaultMeReasoner.query(PclBeliefSet beliefbase, PlFormula formula)
Double	GeneralizedMeReasoner.query(PclBeliefSet beliefbase, PlFormula formula)

Uses of PclBeliefSet in org.tweetyproject.logics.pcl.semantics

Methods in org.tweetyproject.logics.pcl.semantics with parameters of type PclBeliefSet

Modifier and Type	Method	Description
boolean	ProbabilityDistribution.satisfies(PclBeliefSet beliefBase)

Uses of PclBeliefSet in org.tweetyproject.logics.pcl.util

Methods in org.tweetyproject.logics.pcl.util with parameters of type PclBeliefSet

Modifier and Type	Method	Description
static org.ojalgo.matrix.PrimitiveMatrix	OjAlgoPclUtils.createConstraintMatrix(PclBeliefSet beliefSet, Set<PossibleWorld> worlds)	Create constraint matrix for a set of PCL conditionals over a set of possible worlds.
static void	MatlabUtils.printAntecedenceVerificationMatrix(PrintStream out, PclBeliefSet beliefSet, Set<PossibleWorld> worlds)	Print antecedence verification matrix (1 if antecedence is satisfied, 0 otherwise)
static void	MatlabUtils.printConditionalVerificationMatrix(PrintStream out, PclBeliefSet beliefSet, Set<PossibleWorld> worlds)	Print conditional verification matrix (1 if antecedence and consequence are satisfied, 0 otherwise)
static void	MatlabUtils.printConstraintMatrix(PrintStream out, PclBeliefSet beliefSet, Set<PossibleWorld> worlds)	Print constraint matrix for belief set and possible worlds to output stream.