Class PropagationRankingReasoner

  • All Implemented Interfaces:
    net.sf.tweety.commons.ModelProvider<net.sf.tweety.arg.dung.syntax.Argument,​net.sf.tweety.arg.dung.syntax.DungTheory,​LatticeArgumentRanking>, net.sf.tweety.commons.postulates.PostulateEvaluatable<net.sf.tweety.arg.dung.syntax.Argument>

    public class PropagationRankingReasoner
    extends AbstractRankingReasoner<LatticeArgumentRanking>
    This class implements the argument ranking approach of [Delobelle. Ranking- based Semantics for Abstract Argumentation. Thesis, 2017] In this approach, initial values are assigned to arguments and then propagated into the graph. The paper describes three different ways of computing a ranking out of the propagation vector.
    Author:
    Anna Gessler
    • Constructor Detail

      • PropagationRankingReasoner

        public PropagationRankingReasoner​(boolean use_multiset)
        Creates a new PropagationRankingReasoner with the given parameters.
        Parameters:
        use_multiset - determines whether the multiset (M) of attackers/defenders of length is used instead of the set (S)
      • PropagationRankingReasoner

        public PropagationRankingReasoner​(double attacked_arguments_influence,
                                          boolean use_multiset,
                                          PropagationRankingReasoner.PropagationSemantics semantics)
        Creates a new PropagationRankingReasoner with the given parameters.
        Parameters:
        attacked_arguments_influence - the smaller this value is, the more important is the influence of the non-attacked arguments.
        use_multiset - determines whether the multiset (M) of attackers/defenders of length is used instead of the set (S)
        semantics - one of the three propagation semantics