Package net.sf.tweety.logics.pl.util

Class SyntacticRandomSampler

java.lang.Object

net.sf.tweety.commons.BeliefSetSampler<PlFormula,PlBeliefSet>

net.sf.tweety.logics.pl.util.SyntacticRandomSampler

All Implemented Interfaces:

java.util.Iterator<PlBeliefSet>, BeliefSetIterator<PlFormula,PlBeliefSet>

public class SyntacticRandomSampler
extends BeliefSetSampler<PlFormula,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	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.BeliefSetSampler

DEFAULT_MAXIMUM_BELIEFBASE_LENGTH, DEFAULT_MINIMUM_BELIEFBASE_LENGTH

Constructor Summary

Constructors

Constructor	Description
SyntacticRandomSampler(Signature signature, Probability probneg, Probability probconj, Probability probdisj, double recDecrease)	Creates a new sampler.
SyntacticRandomSampler(Signature signature, Probability probneg, Probability probconj, Probability probdisj, double recDecrease, int minLength, int maxLength)	Creates a new sampler.

Method Summary

Modifier and Type	Method	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	next()	Returns the next belief set
PlFormula	sampleFormula(ProbabilityFunction<java.lang.Byte> prob)	Samples a single formula.

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

getMaxLength, getMinLength, getSamplerSignature, hasNext

Methods inherited from class java.lang.Object

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

Methods inherited from interface java.util.Iterator

forEachRemaining, remove

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

SyntacticRandomSampler

public SyntacticRandomSampler(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.

SyntacticRandomSampler

public SyntacticRandomSampler(Signature signature,
                              Probability probneg,
                              Probability probconj,
                              Probability probdisj,
                              double recDecrease,
                              int minLength,
                              int maxLength)

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.

minLength - the minimum length of knowledge bases

maxLength - the maximum length of knowledge bases

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 PlFormula sampleFormula(ProbabilityFunction<java.lang.Byte> prob)

Samples a single formula.

Parameters:

prob - a probability function

Returns:

a single formula.

next

public PlBeliefSet next()

Returns the next belief set

Specified by:

next in interface BeliefSetIterator<PlFormula,PlBeliefSet>

Specified by:

next in interface java.util.Iterator<PlBeliefSet>

Specified by:

next in class BeliefSetSampler<PlFormula,PlBeliefSet>

Returns:

the next belief set