Package org.tweetyproject.arg.dung.learning

Class TheoryLearner

java.lang.Object

org.tweetyproject.arg.dung.learning.TheoryLearner

public class TheoryLearner
extends Object

Improved version of the MaxSAT algorithm from: Niskanen, Andreas, Johannes Wallner, and Matti Järvisalo. "Synthesizing argumentation frameworks from examples." Journal of Artificial Intelligence Research 66 (2019) This algorithm supports 4-valued labelings as proposed in Riveret, Régis, and Guido Governatori. "On learning attacks in probabilistic abstract argumentation." 2016.

Author:

Lars Bengel

Constructor Summary

Constructors

Constructor	Description
TheoryLearner(Collection<Argument> args, Semantics semantics, String solverLocation)	Creates a new theory learner for the given arguments and semantics.

Method Summary

Modifier and Type	Method	Description
DungTheory	learnExamples(Map<Labeling,Integer> positiveExamples, Map<Labeling,Integer> negativeExamples)	Learns an argumentation framework that satisfies as many positive examples as possible while avoiding negative examples.

Methods inherited from class java.lang.Object

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

Constructor Details

TheoryLearner

public TheoryLearner(Collection<Argument> args,
 Semantics semantics,
 String solverLocation)
              throws NoSuchMethodException

Creates a new theory learner for the given arguments and semantics.

Parameters:

args - a set of arguments

semantics - a semantics

solverLocation - path to the open wbo solver binary

Throws:

NoSuchMethodException - if the semantics is not implemented

Method Details

learnExamples

public DungTheory learnExamples(Map<Labeling,Integer> positiveExamples,
 Map<Labeling,Integer> negativeExamples)
                         throws IOException,
InvocationTargetException,
IllegalAccessException

Learns an argumentation framework that satisfies as many positive examples as possible while avoiding negative examples.

Parameters:

positiveExamples - a map of positive examples and their weights

negativeExamples - a map of negative examples and their weights

Returns:

a argumentation framework inferred from the given examples

Throws:

IOException - if an error occurs

InvocationTargetException - if an error occurs

IllegalAccessException - if an error occurs