Package net.sf.tweety.arg.prob.dynamics

Class AbstractPAChangeOperator

java.lang.Object

net.sf.tweety.arg.prob.dynamics.AbstractPAChangeOperator

All Implemented Interfaces:

ChangeOperator

Direct Known Subclasses:

PARevisionOperator, PAUpdateOperator

public abstract class AbstractPAChangeOperator
extends Object
implements ChangeOperator

Provides common functionality for change operators based on probabilistic semantics.

Author:

Matthias Thimm

Field Summary

Fields

Modifier and Type	Field	Description
protected static long	FIRST_OPTIMIZATION_WEIGHT	Optimizations carried out by ancestors of this class perform a two-level optimization.

Constructor Summary

Constructors

Constructor	Description
AbstractPAChangeOperator(PASemantics semantics, net.sf.tweety.math.norm.RealVectorNorm norm, net.sf.tweety.math.func.SimpleRealValuedFunction f)	Creates a new change operator for the given semantics that uses the specified norm for distance measuring and the given function for optimizing.

Method Summary

Modifier and Type	Method	Description
ProbabilisticExtension	change(ProbabilisticExtension p, net.sf.tweety.arg.dung.syntax.DungTheory theory)	Given a probabilistic extension and an argumentation theory, compute the closest probabilistic extension that is adequate for observing the theory in the state p.
abstract ProbabilisticExtension	change(PartialProbabilityAssignment ppa, net.sf.tweety.arg.dung.syntax.DungTheory theory)	Given a partial probability assignment ppa and an argumentation theory, compute the closest probabilistic extension that is adequate for observing the theory in the state ppa.
protected net.sf.tweety.math.func.SimpleRealValuedFunction	getFunction()	Returns the function f.
protected net.sf.tweety.math.norm.RealVectorNorm	getNorm()	Returns the norm.
protected PASemantics	getSemantics()	Returns the semantics.
protected void	prepareOptimizationProblem(PartialProbabilityAssignment ppa, net.sf.tweety.arg.dung.syntax.DungTheory theory, net.sf.tweety.math.opt.problem.OptimizationProblem problem, Map<Collection<net.sf.tweety.arg.dung.syntax.Argument>,net.sf.tweety.math.term.FloatVariable> varsComp, Map<Collection<net.sf.tweety.arg.dung.syntax.Argument>,net.sf.tweety.math.term.FloatVariable> varsSem, Vector<net.sf.tweety.math.term.Term> varsCompVector, Vector<net.sf.tweety.math.term.Term> varsSemVector)

Methods inherited from class java.lang.Object

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

Field Detail

FIRST_OPTIMIZATION_WEIGHT

protected static final long FIRST_OPTIMIZATION_WEIGHT

Optimizations carried out by ancestors of this class perform a two-level optimization. First, one function is minimized and then a second one is maximized. In order to avoid solving two consecutive optimization problems both target functions are combined and the first one is weighted by this factor to give preference.

See Also:

Constant Field Values

Constructor Detail

AbstractPAChangeOperator

public AbstractPAChangeOperator(PASemantics semantics,
                                net.sf.tweety.math.norm.RealVectorNorm norm,
                                net.sf.tweety.math.func.SimpleRealValuedFunction f)

Creates a new change operator for the given semantics that uses the specified norm for distance measuring and the given function for optimizing.

Parameters:

semantics - the semantics used for change.

norm - the norm used for distance measurement between probabilistic extensions.

f - the function that is maximized on the set of probabilistic extensions with minimal distance.

Method Detail

getSemantics

protected PASemantics getSemantics()

Returns the semantics.

Returns:

the semantics.

getNorm

protected net.sf.tweety.math.norm.RealVectorNorm getNorm()

Returns the norm.

Returns:

the norm.

getFunction

protected net.sf.tweety.math.func.SimpleRealValuedFunction getFunction()

Returns the function f.

Returns:

the function f.

change

public abstract ProbabilisticExtension change(PartialProbabilityAssignment ppa,
                                              net.sf.tweety.arg.dung.syntax.DungTheory theory)

Description copied from interface: ChangeOperator

Given a partial probability assignment ppa and an argumentation theory, compute the closest probabilistic extension that is adequate for observing the theory in the state ppa.

Specified by:

change in interface ChangeOperator

Parameters:

ppa - some partial probability assignment.

theory - some theory.

Returns:

the closest probabilistic extension that is adequate for observing the theory in the state ppa.

prepareOptimizationProblem

protected void prepareOptimizationProblem(PartialProbabilityAssignment ppa,
                                          net.sf.tweety.arg.dung.syntax.DungTheory theory,
                                          net.sf.tweety.math.opt.problem.OptimizationProblem problem,
                                          Map<Collection<net.sf.tweety.arg.dung.syntax.Argument>,net.sf.tweety.math.term.FloatVariable> varsComp,
                                          Map<Collection<net.sf.tweety.arg.dung.syntax.Argument>,net.sf.tweety.math.term.FloatVariable> varsSem,
                                          Vector<net.sf.tweety.math.term.Term> varsCompVector,
                                          Vector<net.sf.tweety.math.term.Term> varsSemVector)

change

public ProbabilisticExtension change(ProbabilisticExtension p,
                                     net.sf.tweety.arg.dung.syntax.DungTheory theory)

Description copied from interface: ChangeOperator

Given a probabilistic extension and an argumentation theory, compute the closest probabilistic extension that is adequate for observing the theory in the state p.

Specified by:

change in interface ChangeOperator

Parameters:

p - some probabilistic extension.

theory - some theory.

Returns:

the closest probabilistic extension that is adequate for observing the theory in the state p.