net.sf.tweety.logics.pl.util

Class SyntacticRandomPlBeliefSetSampler

java.lang.Object

net.sf.tweety.commons.BeliefBaseSampler<PlBeliefSet>

net.sf.tweety.logics.pl.util.SyntacticRandomPlBeliefSetSampler

public class SyntacticRandomPlBeliefSetSampler
extends BeliefBaseSampler<PlBeliefSet>

This sampler implements a random generation algorithm for generating formulas, based on the syntax tree of propositional formulas. Consider the following BNF for a propositional logic formula:

F ::== !F | F && F | F || F | A

with propositions A. The algorithm for constructing formulas takes four parameters:

• probneg: the probability to generate a negation
• probconj: the probability to generate a conjunction
• probdisj: the probability to generate a disjunction
• recDecrease: a value in (0,1) by which the above probabilities are multiplied in each recursive step to increase likelihood of termination.

From these parameters the probability to generate a proposition "probprop" is computed via probprop=1-probneg-probconj-probdisj (the actual proposition is selected with a uniform distribution). Then a formula is generated by randomly selecting which rule in the above BNF is followed wrt. these probabilities. Note that the algorithm is not guaranteed to terminate.

Author:

Matthias Thimm

Field Summary

Fields

Modifier and Type	Field and Description
private static byte	CONJ
private static byte	DISJ
private static byte	NEG
private ProbabilityFunction<java.lang.Byte>	prob The probability function modeling the random decisions.
private ProbabilityFunction<Proposition>	probProp The probability function used to sample propositions
private static byte	PROP
private java.util.Random	rand
private double	recDecrease

Fields inherited from class net.sf.tweety.commons.BeliefBaseSampler

DEFAULT_MAXIMUM_BELIEFBASE_LENGTH, DEFAULT_MINIMUM_BELIEFBASE_LENGTH

Constructor Summary

Constructors

Constructor and Description
SyntacticRandomPlBeliefSetSampler(Signature signature, Probability probneg, Probability probconj, Probability probdisj, double recDecrease) Creates a new sampler.

Method Summary

Modifier and Type	Method and Description
private ProbabilityFunction<java.lang.Byte>	decrease(ProbabilityFunction<java.lang.Byte> prob, double value) Adapts the given probability function by decreasing the probabilities of NEG, CONJ and DISJ.
PlBeliefSet	randomSample(int minLength, int maxLength) This method randomly samples a single belief base of the given signature with the given belief base length.
PropositionalFormula	sampleFormula(ProbabilityFunction<java.lang.Byte> prob) Samples a single formula.

Methods inherited from class net.sf.tweety.commons.BeliefBaseSampler

getSignature, randomSample, randomSample

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

prob

private ProbabilityFunction<java.lang.Byte> prob

The probability function modeling the random decisions.

probProp

private ProbabilityFunction<Proposition> probProp

The probability function used to sample propositions

recDecrease

private double recDecrease

NEG

private static final byte NEG

See Also:

Constant Field Values

CONJ

private static final byte CONJ

See Also:

Constant Field Values

DISJ

private static final byte DISJ

See Also:

Constant Field Values

PROP

private static final byte PROP

See Also:

Constant Field Values

rand

private java.util.Random rand

Constructor Detail

SyntacticRandomPlBeliefSetSampler

public SyntacticRandomPlBeliefSetSampler(Signature signature,
                                         Probability probneg,
                                         Probability probconj,
                                         Probability probdisj,
                                         double recDecrease)

Creates a new sampler.

Parameters:

signature - some set of propositions

probneg - the probability to generate a negation

probconj - the probability to generate a conjunction

probdisj - the probability to generate a disjunction

recDecrease - a value in (0,1) by which the above probabilities are multiplied in each recursive step to increase likelihood of termination.

Method Detail

decrease

private ProbabilityFunction<java.lang.Byte> decrease(ProbabilityFunction<java.lang.Byte> prob,
                                                     double value)

Adapts the given probability function by decreasing the probabilities of NEG, CONJ and DISJ.

Parameters:

prob - a probability function.

value - some value in (0,1)

Returns:

the modified probability function.

sampleFormula

public PropositionalFormula sampleFormula(ProbabilityFunction<java.lang.Byte> prob)

Samples a single formula.

Returns:

a single formula.

randomSample

public PlBeliefSet randomSample(int minLength,
                                int maxLength)

Description copied from class: BeliefBaseSampler

This method randomly samples a single belief base of the given signature with the given belief base length.

Specified by:

randomSample in class BeliefBaseSampler<PlBeliefSet>

Parameters:

minLength - the minimum length of the belief base.

maxLength - the maximum length of the belief base.

Returns:

a single belief base.