net.sf.tweety.logics.cl.reasoner

Class BruteForceCReasoner

java.lang.Object

net.sf.tweety.logics.cl.reasoner.AbstractConditionalLogicReasoner

net.sf.tweety.logics.cl.reasoner.BruteForceCReasoner

All Implemented Interfaces:

ModelProvider<Conditional,ClBeliefSet,RankingFunction>, QualitativeReasoner<ClBeliefSet,PropositionalFormula>, Reasoner<java.lang.Boolean,ClBeliefSet,PropositionalFormula>

public class BruteForceCReasoner
extends AbstractConditionalLogicReasoner

This class models a brute force c-reasoner for conditional logic. Reasoning is performed by computing a minimal c-representation for the given knowledge base.
A c-representation for a conditional knowledge base R={r1,...,rn} is a ranking function k such that k accepts every conditional in R (k |= R) and if there are numbers k0,k1+,k1-,...,kn+,kn- with
k(w)=k0 + \sum_{w verifies ri} ki+ + \sum_{w falsifies ri} kj- for every w. A c-representation is minimal if k0+...+kn- is minimal.
The c-representation is computed using a brute force approach.

See Gabriele Kern-Isberner. Conditionals in nonmonotonic reasoning and belief revision. Lecture Notes in Computer Science, Volume 2087. 2001.

Author:

Matthias Thimm

Field Summary

Fields

Modifier and Type	Field and Description
private java.util.Map<java.lang.Integer,Conditional>	indexToConditional Maps the indices of the kappa vector to their corresponding conditionals.
private java.util.List<java.lang.Integer[]>	kappa The current vectors of kappa values.
private int	numConditionals The number of conditionals in the given knowledge base.
private boolean	simple indicates whether the computed c-representation is simple.

Constructor Summary

Constructors

Constructor and Description
BruteForceCReasoner() Creates a new simple c-representation reasoner.
BruteForceCReasoner(boolean simple) Creates a new c-representation reasoner

Method Summary

Modifier and Type	Method and Description
private RankingFunction	constructRankingFunction(ClBeliefSet beliefset, java.lang.Integer[] kappa) Constructs a ranking function with the given kappa values [k1+,k1-,...,kn+,kn-], i.e.
private void	filter(java.util.ArrayList<PropositionalFormula> list, ClBeliefSet beliefset)
RankingFunction	getModel(ClBeliefSet beliefset) Returns a single (dedicated) model of the given belief base.
private java.lang.Integer[]	increment(java.lang.Integer[] kappa) This method increments the given array by one value.
private boolean	incrementStep(java.lang.Integer[] kappaRow) This method increments the given vector (which composes of exactly one "1" entry and zeros otherwise), e.g.

Methods inherited from class net.sf.tweety.logics.cl.reasoner.AbstractConditionalLogicReasoner

getModels, query

Methods inherited from class java.lang.Object

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

Field Detail

kappa

private java.util.List<java.lang.Integer[]> kappa

The current vectors of kappa values.

numConditionals

private int numConditionals

The number of conditionals in the given knowledge base.

indexToConditional

private java.util.Map<java.lang.Integer,Conditional> indexToConditional

Maps the indices of the kappa vector to their corresponding conditionals.

simple

private boolean simple

indicates whether the computed c-representation is simple.

Constructor Detail

BruteForceCReasoner

public BruteForceCReasoner(boolean simple)

Creates a new c-representation reasoner

Parameters:

simple - whether the computed c-representation is simple.

BruteForceCReasoner

public BruteForceCReasoner()

Creates a new simple c-representation reasoner.

Parameters:

beliefBase - a knowledge base.

Method Detail

filter

private void filter(java.util.ArrayList<PropositionalFormula> list,
                    ClBeliefSet beliefset)

constructRankingFunction

private RankingFunction constructRankingFunction(ClBeliefSet beliefset,
                                                 java.lang.Integer[] kappa)

Constructs a ranking function with the given kappa values [k1+,k1-,...,kn+,kn-], i.e. for every possible world w set
k(w)=k0 + \sum_{w verifies ri} ki+ + \sum_{w falsifies ri} kj-

Parameters:

kappa -

increment

private java.lang.Integer[] increment(java.lang.Integer[] kappa)

This method increments the given array by one value.

Parameters:

kappa - an array of integers.

Returns:

an array of integers.

incrementStep

private boolean incrementStep(java.lang.Integer[] kappaRow)

This method increments the given vector (which composes of exactly one "1" entry and zeros otherwise), e.g. [0,0,1,0] -> [0,0,0,1] and [0,0,0,1] -> [1,0,0,0]

Parameters:

kappaRow - a vector of zeros and one "1"

Returns:

"true" if there is an overflow, i.e. when [0,0,0,1] -> [1,0,0,0], otherwise "false".

getModel

public RankingFunction getModel(ClBeliefSet beliefset)

Description copied from interface: ModelProvider

Returns a single (dedicated) model of the given belief base. If the implemented method allows for more than one dedicated model, the selection may be non-deterministic.

Specified by:

getModel in interface ModelProvider<Conditional,ClBeliefSet,RankingFunction>

Specified by:

getModel in class AbstractConditionalLogicReasoner

Returns:

a selected model of the belief base.