Package org.tweetyproject.arg.dung.learning

Class ImprovedRiveretTheoryLearner

java.lang.Object

org.tweetyproject.arg.dung.learning.ImprovedRiveretTheoryLearner

public class ImprovedRiveretTheoryLearner
extends Object

Implementation of the algorithm for learning (grounded) labelings from with some improvements: Riveret, Régis, and Guido Governatori. "On learning attacks in probabilistic abstract argumentation." 2016. - improves result for argumentation frameworks with self-attacking arguments - instead of stopping when no undecided attacks are left, we always use the full computational budget - added additional parameter for pruning instead of pruning at 0. eg budget: 500 threshold: -10 - added fifth rule to capture self-attacking arguments - extended rule 3 - adjusted weight updates per rule

Author:

Lars Bengel

Constructor Summary

Constructors

Constructor	Description
ImprovedRiveretTheoryLearner(Collection<Argument> arguments, int max_cycles)	initialize learner for the given set of arguments

Method Summary

Modifier and Type	Method	Description
DungTheory	learnLabelings(ArrayList<Labeling> labelings)	learn theory without pruning discarded attacks
DungTheory	learnLabelings(ArrayList<Labeling> labelings, boolean prune, int threshold)	learn random labelings from the given List until no undecided attacks are left in the theory
void	showWeights()	show Weights

Methods inherited from class java.lang.Object

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

Constructor Details

ImprovedRiveretTheoryLearner

public ImprovedRiveretTheoryLearner(Collection<Argument> arguments,
 int max_cycles)

initialize learner for the given set of arguments

Parameters:

arguments - a set of arguments

max_cycles - the maximal number of cycles

Method Details

showWeights

public void showWeights()

show Weights

learnLabelings

public DungTheory learnLabelings(ArrayList<Labeling> labelings,
 boolean prune,
 int threshold)

learn random labelings from the given List until no undecided attacks are left in the theory

Parameters:

labelings - a list of labelings

prune - if true, remove discarded attacks after each step

threshold - the treshold

Returns:

the learned dung theory

learnLabelings

public DungTheory learnLabelings(ArrayList<Labeling> labelings)

learn theory without pruning discarded attacks

Parameters:

labelings - a list of labelings

Returns:

the learned dung theory