Package net.sf.tweety.arg.prob.lotteries

Class SubgraphProbabilityFunction

java.lang.Object

net.sf.tweety.math.probability.ProbabilityFunction<DungTheory>

net.sf.tweety.arg.prob.lotteries.SubgraphProbabilityFunction

All Implemented Interfaces:

java.util.Map<DungTheory,Probability>

public class SubgraphProbabilityFunction
extends ProbabilityFunction<DungTheory>

Represents a probability function on the subgraphs of some Dung theory.

Author:

Matthias Thimm

Nested Class Summary

Nested classes/interfaces inherited from interface java.util.Map

java.util.Map.Entry<K extends java.lang.Object,V extends java.lang.Object>

Constructor Summary

Constructors

Constructor	Description
SubgraphProbabilityFunction(DungTheory theory)	Creates a new uniform probability function for the given theory, i.e.

Method Summary

Modifier and Type	Method	Description
Probability	getAcceptanceProbability(Division d, Semantics semantics)	Returns the probability of the given division being acceptable wrt.
Probability	getAcceptanceProbability(LdoFormula f, Semantics semantics)	Returns the probability of the given formula being acceptable wrt.
Probability	getAcceptanceProbability(Extension ext, Semantics semantics)	Returns the probability of the given set of arguments being acceptable wrt.
Probability	getAcceptanceProbability(Argument arg, Semantics semantics)	Returns the probability of the given argument being acceptable wrt.
Probability	getEpistemicProbability(Argument arg)	Returns the epistemic probability of the given argument, i.e.
Probability	getEpistemicProbability(Attack att)	Returns the epistemic probability of the given attack, i.e.
DungTheory	getTheory()	Returns the theory of this probability function.
SubgraphProbabilityFunction	naiveUpdate(Extension e)	Updates this probability function with the given extension, i.e.
SubgraphProbabilityFunction	roughUpdate(DungTheory theory)	Updates this probability function with the given theory using "rough redistribution", cf.
SubgraphProbabilityFunction	simpleUpdate(DungTheory theory)	Updates this probability function with the given theory using "simple redistribution", cf.
SubgraphProbabilityFunction	stickyUpdate(DungTheory theory, double stickyCoefficient)	Updates this probability function with the given theory using "sticky redistribution", cf.

Methods inherited from class net.sf.tweety.math.probability.ProbabilityFunction

clear, containsKey, containsValue, convexCombination, convexCombination, entrySet, equals, get, getProbabilityVector, getProbabilityVectorAsDoubles, getUniformDistribution, hashCode, isEmpty, isNormalized, keySet, linearCombination, normalize, probability, probability, put, putAll, remove, sample, sample, size, toString, values

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map

compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

Constructor Detail

SubgraphProbabilityFunction

public SubgraphProbabilityFunction(DungTheory theory)

Creates a new uniform probability function for the given theory, i.e. all sub graphs of the given theory receive the same probability.

Parameters:

theory - some theory.

Method Detail

getTheory

public DungTheory getTheory()

Returns the theory of this probability function.

Returns:

the theory of this probability function.

getEpistemicProbability

public Probability getEpistemicProbability(Argument arg)

Returns the epistemic probability of the given argument, i.e. the probability that the given argument is present in some randomly sampled sub graph.

Parameters:

arg - some argument

Returns:

a probability

getEpistemicProbability

public Probability getEpistemicProbability(Attack att)

Returns the epistemic probability of the given attack, i.e. the probability that the given attack is present in some randomly sampled sub graph.

Parameters:

att - some attack

Returns:

a probability

getAcceptanceProbability

public Probability getAcceptanceProbability(LdoFormula f,
                                            Semantics semantics)

Returns the probability of the given formula being acceptable wrt. the given semantics and this probability function, i.e. the sum of the probabilities of all sub-graphs that are dividers of the given formula.

Parameters:

f - some formula

semantics - some semantics.

Returns:

a probability

getAcceptanceProbability

public Probability getAcceptanceProbability(Division d,
                                            Semantics semantics)

Returns the probability of the given division being acceptable wrt. the given semantics and this probability function, i.e. the sum of the probabilities of all sub-graphs that are dividers of the given division.

Parameters:

d - some division

semantics - some semantics.

Returns:

a probability

getAcceptanceProbability

public Probability getAcceptanceProbability(Argument arg,
                                            Semantics semantics)

Returns the probability of the given argument being acceptable wrt. the given semantics and this probability functions. This is equivalent to the probability of the division ({arg},{}).

Parameters:

arg - some argument

semantics - some semantics.

Returns:

a probability

getAcceptanceProbability

public Probability getAcceptanceProbability(Extension ext,
                                            Semantics semantics)

Returns the probability of the given set of arguments being acceptable wrt. the given semantics and this probability functions. This is equivalent to the probability of the division (ext,{}).

Parameters:

ext - some set of arguments

semantics - some semantics.

Returns:

a probability

naiveUpdate

public SubgraphProbabilityFunction naiveUpdate(Extension e)

Updates this probability function with the given extension, i.e. all theories that do not contain the given arguments get probability zero. Afterwards the function is normalized.

Parameters:

e - some extension

Returns:

the updated probability function

simpleUpdate

public SubgraphProbabilityFunction simpleUpdate(DungTheory theory)

Updates this probability function with the given theory using "simple redistribution", cf. [Hunter, Thimm, 2015].

Parameters:

theory - some abstract theory

Returns:

the updated probability function

stickyUpdate

public SubgraphProbabilityFunction stickyUpdate(DungTheory theory,
                                                double stickyCoefficient)

Updates this probability function with the given theory using "sticky redistribution", cf. [Hunter, Thimm, 2015].

Parameters:

theory - some abstract theory

stickyCoefficient - the sticky coefficient

Returns:

the updated probability function

roughUpdate

public SubgraphProbabilityFunction roughUpdate(DungTheory theory)

Updates this probability function with the given theory using "rough redistribution", cf. [Hunter, Thimm, 2015].

Parameters:

theory - some abstract theory

Returns:

the updated probability function