OjAlgoPclUtils

java.lang.Object

org.tweetyproject.logics.pcl.util.OjAlgoPclUtils

public class OjAlgoPclUtils extends Object

Provides some utility functions for solving Pcl specific reasoning problems with ojAlgo.

Author:: NicoPotyka

Constructor Summary

Constructors

Constructor

Description

OjAlgoPclUtils()

Default Constructor
Method Summary

Modifier and Type

Method

Description

static void

addProbabilityNormalizationConstraint(org.ojalgo.optimisation.ExpressionsBasedModel model)

Add probability normalization constraint to model (all probabilities have to sum to 1).

static org.ojalgo.matrix.PrimitiveMatrix

createConstraintMatrix(PclBeliefSet beliefSet, Set<PossibleWorld> worlds)

Create constraint matrix for a set of PCL conditionals over a set of possible worlds.

static org.ojalgo.optimisation.Variable[]

createVariables(int noWorlds)

Create (non-negative) variables for the probabilities of possible worlds.

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details
- OjAlgoPclUtils
  
  public OjAlgoPclUtils()
  
  Default Constructor
Method Details
- addProbabilityNormalizationConstraint
  
  public static void addProbabilityNormalizationConstraint(org.ojalgo.optimisation.ExpressionsBasedModel model)
  
  Add probability normalization constraint to model (all probabilities have to sum to 1).
  
  Parameters:
  
  model - the model
- createVariables
  
  public static org.ojalgo.optimisation.Variable[] createVariables(int noWorlds)
  
  Create (non-negative) variables for the probabilities of possible worlds.
  
  Parameters:
  
  noWorlds - the number of worlds
  
  Returns:
  
  the variables
- createConstraintMatrix
  
  public static org.ojalgo.matrix.PrimitiveMatrix createConstraintMatrix(PclBeliefSet beliefSet, Set<PossibleWorld> worlds)
  
  Create constraint matrix for a set of PCL conditionals over a set of possible worlds.
  
  Parameters:
  
  beliefSet - a belief set
  
  worlds - a set of possible worlds
  
  Returns:
  
  the constraint matrix