20 research outputs found
Extending Modular Semantics for Bipolar Weighted Argumentation (Technical Report)
Weighted bipolar argumentation frameworks offer a tool for decision support
and social media analysis. Arguments are evaluated by an iterative procedure
that takes initial weights and attack and support relations into account. Until
recently, convergence of these iterative procedures was not very well
understood in cyclic graphs. Mossakowski and Neuhaus recently introduced a
unification of different approaches and proved first convergence and divergence
results. We build up on this work, simplify and generalize convergence results
and complement them with runtime guarantees. As it turns out, there is a
tradeoff between semantics' convergence guarantees and their ability to move
strength values away from the initial weights. We demonstrate that divergence
problems can be avoided without this tradeoff by continuizing semantics.
Semantically, we extend the framework with a Duality property that assures a
symmetric impact of attack and support relations. We also present a Java
implementation of modular semantics and explain the practical usefulness of the
theoretical ideas
Coalitions of Arguments: An Approach with Constraint Programming
The aggregation of generic items into coalitions leads to the creation of sets of homogenous entities. In this paper we accomplish this for an input set of arguments, and the result is a partition according to distinct lines of thought, i.e., groups of "coherent" ideas. We extend Dung\u27s Argumentation Framework (AF) in order to deal with coalitions of arguments. The initial set of arguments is partitioned into not-intersected subsets. All the found coalitions show the same property inherited by Dung, e.g., all the coalitions in the partition are admissible (or conflict-free, complete, stable): they are generated according to Dung\u27s principles. Each of these coalitions can be assigned to a different agent. We use Soft Constraint Programming as a formal approach to model and solve such partitions in weighted AFs: semiring algebraic structures can be used to model different optimization criteria for the obtained coalitions. Moreover, we implement and solve the presented problem with JaCoP, a Java constraint solver, and we test the code over a small-world network
An Efficient Java-Based Solver for Abstract Argumentation Frameworks: jArgSemSAT
Dung’s argumentation frameworks are adopted in a variety of applications, from
argument-mining, to intelligence analysis and legal reasoning. Despite this broad spectrum
of already existing applications, the mostly adopted solver—in virtue of its
simplicity—is far from being comparable to the current state-of-the-art solvers. On the
other hand, most of the current state-of-the-art solvers are far too complicated to be
deployed in real-world settings. In this paper we provide and extensive description of
jArgSemSAT, a Java re-implementation of ArgSemSAT. ArgSemSAT represents the best
single solver for argumentation semantics with the highest level of computational complexity.
We show that jArgSemSAT can be easily integrated in existing argumentation
systems (1) as an off-the-shelf, standalone, library; (2) as a Tweety compatible library;
and (3) as a fast and robust web service freely available on the Web. Our large experimental
analysis shows that—despite being written in Java—jArgSemSAT would have
scored in most of the cases among the three bests solvers for the two semantics with
highest computational complexity—Stable and Preferred—in the last competition on
computational models of argumentation