| Modifier and Type | Method and Description | 
|---|---|
Probability | 
DelpRule.getUniformProbability()  | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
LdoFormula.getUniformProbability()  | 
| Modifier and Type | Field and Description | 
|---|---|
private java.util.Map<Argument,Probability> | 
ProbabilisticArgumentationFramework.argumentProbabilityAssignment
Probability assignments to arguments (with independence assumption). 
 | 
private java.util.Map<Attack,Probability> | 
ProbabilisticArgumentationFramework.attackProbabilityAssignment
Probability assignments to attacks (with independence assumption). 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
ProbabilisticArgumentationFramework.getProbability(Argument a)
Returns the probability of the given argument. 
 | 
Probability | 
ProbabilisticArgumentationFramework.getProbability(Attack a)
Returns the probability of the given attack. 
 | 
Probability | 
ProbabilisticArgumentationFramework.getProbability(DungTheory aaf)
Computes the probability of the given AAF wrt. 
 | 
Probability | 
MonteCarloPafReasoner.query(Extension ext)
Estimates the probability that the given set of
 arguments is an extension 
 | 
| Modifier and Type | Method and Description | 
|---|---|
boolean | 
ProbabilisticArgumentationFramework.add(Argument a,
   Probability p)
Adds the given argument with the given probability 
 | 
boolean | 
ProbabilisticArgumentationFramework.add(Attack att,
   Probability p)
Adds the given attack with the given probability 
 | 
| Modifier and Type | Field and Description | 
|---|---|
private java.util.Map<LdoFormula,Probability> | 
LdoArgumentationLottery.prob
Maps LdoFormulas to probabilities 
 | 
private java.util.Map<Division,Probability> | 
ArgumentationLottery.prob
Maps divisions to probabilities 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
ArgumentationLottery.get(Division d)
Returns the probability of the given outcome. 
 | 
Probability | 
LdoArgumentationLottery.get(LdoFormula f)
Returns the probability of the given outcome. 
 | 
Probability | 
SubgraphProbabilityFunction.getAcceptanceProbability(Argument arg,
                        Semantics semantics)
Returns the probability of the given argument being acceptable wrt. 
 | 
Probability | 
SubgraphProbabilityFunction.getAcceptanceProbability(Division d,
                        Semantics semantics)
Returns the probability of the given division being acceptable wrt. 
 | 
Probability | 
SubgraphProbabilityFunction.getAcceptanceProbability(Extension ext,
                        Semantics semantics)
Returns the probability of the given set of arguments being acceptable wrt. 
 | 
Probability | 
SubgraphProbabilityFunction.getAcceptanceProbability(LdoFormula f,
                        Semantics semantics)
Returns the probability of the given formula being acceptable wrt. 
 | 
Probability | 
SubgraphProbabilityFunction.getEpistemicProbability(Argument arg)
Returns the epistemic probability of the given argument, i.e. 
 | 
Probability | 
SubgraphProbabilityFunction.getEpistemicProbability(Attack att)
Returns the epistemic probability of the given attack, i.e. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
ProbabilisticExtension.probability(Argument a)
Computes the probability of the given argument. 
 | 
| Modifier and Type | Field and Description | 
|---|---|
private java.util.Map<PropositionalFormula,Probability> | 
DeductiveProbabilisticKnowledgebase.probabilityAssignments
Probability assignments for formulas. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
java.util.Map<PropositionalFormula,Probability> | 
DeductiveProbabilisticKnowledgebase.getProbabilityAssignments()
Returns the probability assignments 
 | 
| Constructor and Description | 
|---|
DeductiveProbabilisticKnowledgebase(DeductiveKnowledgeBase kb,
                                   java.util.Map<PropositionalFormula,Probability> probabilityAssignments)
Creates a new probabilistic knowledge base from the given parameters. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
ProbabilityAware.getUniformProbability()  | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
ModalFormula.getUniformProbability()  | 
| Modifier and Type | Method and Description | 
|---|---|
abstract Probability | 
RelationalFormula.getUniformProbability()  | 
Probability | 
FolFormula.getUniformProbability()  | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
MlnFormula.getUniformProbability()  | 
| Constructor and Description | 
|---|
MlnFormula(FolFormula formula,
          Probability p)
Creates a new MLN formula and estimates its weight w by the given
 probability p using the formula w = log(p/(1-p)*f) where "f" is the
 ratio of the number of worlds not satisfying the formula and the
 worlds satisfying the formula. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected java.util.Map<ProbabilisticConditional,Probability> | 
UnbiasedCreepingMachineShop.getValues(double delta,
         PclBeliefSet beliefSet)  | 
protected java.util.Map<ProbabilisticConditional,Probability> | 
SmoothedPenalizingCreepingMachineShop.getValues(double delta,
         PclBeliefSet beliefSet)  | 
protected java.util.Map<ProbabilisticConditional,Probability> | 
PenalizingCreepingMachineShop.getValues(double delta,
         PclBeliefSet beliefSet)  | 
protected abstract java.util.Map<ProbabilisticConditional,Probability> | 
AbstractCreepingMachineShop.getValues(double delta,
         PclBeliefSet beliefSet)
Computes the values of the conditionals for step delta 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected PclBeliefSet | 
AbstractCreepingMachineShop.characteristicFunction(PclBeliefSet beliefSet,
                      java.util.Map<ProbabilisticConditional,Probability> values)
Returns a modified belief base that replaces each conditionals probability
 by the one given by "values". 
 | 
| Modifier and Type | Field and Description | 
|---|---|
private java.util.Map<T,Probability> | 
ProbabilityDistribution.probabilities
The probabilities of the interpretations. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
ProbabilityDistribution.conditionalProbability(Conditional c)
Returns the probability of the given conditional 
 | 
Probability | 
ProbabilityDistribution.get(java.lang.Object key)  | 
Probability | 
ProbabilityDistribution.probability(Formula f)
Returns the probability of the given formula 
 | 
Probability | 
ProbabilityDistribution.probability(Interpretation w)
Gets the probability of the given Herbrand interpretation (this is just an
 alias for get(Object o). 
 | 
Probability | 
ProbabilityDistribution.put(T key,
   Probability value)  | 
Probability | 
ProbabilityDistribution.remove(java.lang.Object key)  | 
| Modifier and Type | Method and Description | 
|---|---|
java.util.Set<java.util.Map.Entry<T,Probability>> | 
ProbabilityDistribution.entrySet()  | 
java.util.Collection<Probability> | 
ProbabilityDistribution.values()  | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
ProbabilityDistribution.put(T key,
   Probability value)  | 
| Modifier and Type | Method and Description | 
|---|---|
void | 
ProbabilityDistribution.putAll(java.util.Map<? extends T,? extends Probability> m)  | 
| Modifier and Type | Field and Description | 
|---|---|
private Probability | 
ProbabilisticConditional.probability
The probability of this conditional. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
ProbabilisticConditional.getProbability()
Returns the probability of this conditional. 
 | 
Probability | 
ProbabilisticConditional.getUniformProbability()  | 
| Constructor and Description | 
|---|
ProbabilisticConditional(Conditional conditional,
                        Probability probability)
Creates a new probabilistic conditional using the given conditional
 and probability. 
 | 
ProbabilisticConditional(PropositionalFormula conclusion,
                        Probability probability)
Creates a new probabilistic conditional with a tautological premise
 and given conclusion and probability. 
 | 
ProbabilisticConditional(PropositionalFormula premise,
                        PropositionalFormula conclusion,
                        Probability probability)
Creates a new probabilistic conditional with the given premise,
 conclusion, and probability. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
PropositionalFormula.getUniformProbability()
Returns this formula's probability in the uniform distribution. 
 | 
| Constructor and Description | 
|---|
SyntacticRandomPlBeliefSetSampler(Signature signature,
                                 Probability probneg,
                                 Probability probconj,
                                 Probability probdisj,
                                 double recDecrease)
Creates a new sampler. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
RelationalConditional.getUniformProbability()  | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
DefaultRule.getUniformProbability()  | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
CondensedProbabilityDistribution.probability(FolFormula f)  | 
| Modifier and Type | Method and Description | 
|---|---|
static Pair<ReferenceWorld,Probability> | 
RpclCondensedProbabilityDistributionParser.ProbabilityAssignment(FolSignature signature)  | 
| Modifier and Type | Method and Description | 
|---|---|
static Pair<HerbrandInterpretation,Probability> | 
RpclProbabilityDistributionParser.ProbabilityAssignment(FolSignature signature)  | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
RpclProbabilityDistribution.probability(FolFormula f)
Gets the probability of the given closed formula, i.e. 
 | 
Probability | 
RpclProbabilityDistribution.probability(RelationalConditional re)
Gets the probability of the given closed relational conditional "re", i.e. 
 | 
| Modifier and Type | Field and Description | 
|---|---|
private Probability | 
RelationalProbabilisticConditional.probability
The probability of the formula. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
RelationalProbabilisticConditional.getProbability()
Returns the probability of this conditional. 
 | 
| Constructor and Description | 
|---|
RelationalProbabilisticConditional(FolFormula premise,
                                  FolFormula conclusion,
                                  Probability probability)
Creates a new conditional with the given premise, conclusion and probability. 
 | 
RelationalProbabilisticConditional(FolFormula conclusion,
                                  Probability probability)
Creates a new conditional with the given conclusion and probability and
 a tautological premise. 
 | 
RelationalProbabilisticConditional(RelationalConditional conditional,
                                  Probability probability)
Creates a new relational probabilistic conditional with the given conditional and probability 
 | 
| Modifier and Type | Field and Description | 
|---|---|
static Probability | 
Probability.ONE
Constant for probability 1 
 | 
static Probability | 
Probability.ZERO
Constant for probability 0 
 | 
| Modifier and Type | Field and Description | 
|---|---|
private java.util.Map<T,Probability> | 
ProbabilityFunction.probabilities
The probabilities of the objects. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
Probability.add(Probability other)
Computes the sum of this and the given probability. 
 | 
Probability | 
Probability.complement()
Returns the complement of this probability, i.e. 
 | 
Probability | 
Probability.divide(java.lang.Double other)
Divides this probability by given value returns the result. 
 | 
Probability | 
Probability.divide(Probability other)
Divides this probability by other and returns the result. 
 | 
Probability | 
ProbabilityFunction.get(java.lang.Object key)  | 
Probability | 
Probability.mult(java.lang.Double other)
Computes the product of this probability and the given number. 
 | 
Probability | 
Probability.mult(java.lang.Integer other)
Computes the product of this probability and the given number. 
 | 
Probability | 
Probability.mult(Probability other)
Computes the product of this probability and the given probability. 
 | 
Probability | 
ProbabilityFunction.probability(java.util.Collection<? extends T> objects)
Gets the probability of the given object. 
 | 
Probability | 
ProbabilityFunction.probability(T w)
Gets the probability of the given object. 
 | 
Probability | 
ProbabilityFunction.put(T key,
   Probability value)  | 
Probability | 
ProbabilityFunction.remove(java.lang.Object key)  | 
| Modifier and Type | Method and Description | 
|---|---|
java.util.Set<java.util.Map.Entry<T,Probability>> | 
ProbabilityFunction.entrySet()  | 
java.util.Vector<Probability> | 
ProbabilityFunction.getProbabilityVector()
Returns the vector of probabilities, depending on the order
 of the domain elements (which can be ordered as they
 implement Comparable). 
 | 
java.util.Collection<Probability> | 
ProbabilityFunction.values()  | 
| Modifier and Type | Method and Description | 
|---|---|
Probability | 
Probability.add(Probability other)
Computes the sum of this and the given probability. 
 | 
Probability | 
Probability.divide(Probability other)
Divides this probability by other and returns the result. 
 | 
boolean | 
Probability.isWithinTolerance(Probability other)
Checks whether the given probability is "nearly" the same
 as this probability (given the actual precision). 
 | 
Probability | 
Probability.mult(Probability other)
Computes the product of this probability and the given probability. 
 | 
Probability | 
ProbabilityFunction.put(T key,
   Probability value)  | 
| Modifier and Type | Method and Description | 
|---|---|
void | 
ProbabilityFunction.putAll(java.util.Map<? extends T,? extends Probability> m)  | 
| Constructor and Description | 
|---|
Probability(Probability other)
Creates a new probability from the given probability 
 |