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

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

Synthesizing Argumentation Frameworks from Examples

Peer reviewe

On the Impact of Configuration on Abstract Argumentation Automated Reasoning

In this paper we consider the impact of configuration of abstract argumentation reasoners both when using a single solver and choosing combinations of framework representation–solver options; and also when composing portfolios of algorithms. To exemplify the impact of the framework–solver configuration we consider one of the most configurable solvers, namely ArgSemSAT—runner-up of the last competition on computational models of argumentation (ICCMA-15)—for enumerating preferred extensions. We discuss how to configure the representation of the argumentation framework in the input file and show how this coupled framework–solver configuration can have a remarkable impact on performance. As to the impact of configuring differently structured portfolios of abstract argumentation solvers, we consider the solvers submitted to ICCMA-15, which provided the community with a heterogeneous panorama of approaches for handling abstract argumentation frameworks. A superficial reading of the results of ICCMA-15 is that reduction-based systems (either SAT-based or ASP-based) are always the most efficient. Our investigation, concerning the enumeration of stable and preferred extensions, shows that this is not true in full generality and suggests the areas where the relatively under-developed non reduction-based systems should focus more to improve their performance. Moreover, it also highlights that the state-of-the-art solvers are very complementary and can be successfully combined in portfolios