Summary Report of the First International Competition on Computational Models of Argumentation

Thimm, Matthias; Villata, Serena; Cerutti, Federico; Oren, Nir; Straß, Hannes; Vallati, Mauro

doi:10.1609/aimag.v37i1.2640

Cited by 41 publications

(41 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The second empirical experiment is to study the performance effects of using basic querying and advance querying to compute ST and CO semantics. We also compare our approach with a modern solver ArgSemSAT [12], which received the awards of "Second Place" of ICCMA2015 [17]. We consider to execute our tests by using the benchmark argument graphs from [18], where the authors randomly generate AFs according to two parameterized graph models: Kleinberg, and the Barabasi-Albert models † .…”

Section: Methodsmentioning

confidence: 99%

Encoding Argumentation Semantics by Boolean Algebra

Luo

Zhou

2017

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARYIn this paper, a Boolean algebra approach is proposed to encode various acceptability semantics for abstract argumentation frameworks, where each semantics can be equivalently encoded into several Boolean constraint models based on Boolean matrices and a family of Boolean operations between them. Then, we show that these models can be easily translated into logic programs, and can be solved by a constraint solver over Boolean variables. In addition, we propose some querying strategies to accelerate the calculation of the grounded, stable and complete extensions. Finally, we describe an experimental study on the performance of our encodings according to different semantics and querying strategies.

show abstract

Section: Methodsmentioning

confidence: 99%

Encoding Argumentation Semantics by Boolean Algebra

Luo

Zhou

2017

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

show abstract

“…The argumentation solver competition 2015 [51] had eleven participating systems in the task of deciding skeptical acceptance of an argument w.r.t. preferred semantics.…”

Section: Related Workmentioning

confidence: 99%

“…Thus, efficient and advanced algorithms have to be developed in order to deal with real-world size data within reasonable performance bounds. The argumentation community is currently facing this challenge [17]: Already the second edition [27] of the solver competition [50,51] was held in 2017. Thus, the number of new algorithms and systems is steadily increasing, and we expect this to continue in the (near) future.…”

Section: Introductionmentioning

confidence: 99%

Abstract solvers for Dung’s argumentation frameworks

Brochenin

Linsbichler

Maratea

et al. 2018

AAC

View full text Add to dashboard Cite

TU Wien, Austria E-mails: linsbich@dbai.tuwien.ac.at, wallner@dbai.tuwien.ac.at, woltran@dbai.tuwien.ac.at Abstract. Abstract solvers are a quite recent method to uniformly describe algorithms in a rigorous formal way via graphs. Compared to traditional methods like pseudo-code descriptions, abstract solvers have several advantages. In particular, they provide a uniform formal representation that allows for precise comparisons of different algorithms. Recently, this new methodology has proven successful in declarative paradigms such as Propositional Satisfiability and Answer Set Programming. In this paper, we apply this machinery to Dung's abstract argumentation frameworks. We first provide descriptions of several advanced algorithms for the preferred semantics in terms of abstract solvers. We also show how it is possible to obtain new abstract solutions by "combining" concepts of existing algorithms by means of combining abstract solvers. Then, we implemented a new solving procedure based on our findings in CEGARTIX, and call it CEGARTIX+. We finally show that CEGARTIX+ is competitive and complementary in its performance to CEGARTIX on benchmarks of the first and second argumentation competition.Keywords: Abstract argumentation, abstract solvers IntroductionDung's concept of abstract argumentation [23] is nowadays a core formalism in Artificial Intelligence [4,46]. The problem of solving certain reasoning tasks on such frameworks is the centerpiece of many advanced higher-level argumentation systems. The problems to be solved can however be intractable and might even be hard for the second level of the polynomial hierarchy [24,26]. Thus, efficient and advanced algorithms have to be developed in order to deal with real-world size data within reasonable performance bounds. The argumentation community is currently facing this challenge [17] [44]. Hereby, one characterizes the possible states of computation as nodes of a graph, and the techniques (i.e., the computation steps in the algorithms) as arcs between nodes. In this way, the whole solving process amounts to a path in the graph. This concept proved successful for SAT [44], and also has been applied to several variants of Answer Set Programming [6,36,37].In this paper, we apply abstract solvers to certain problems in Dung's argumentation frameworks. In order to understand whether abstract solvers are well suited also for this domain, we consider quite advanced algorithms for solving problems that are hard for the second level of the polynomial hierarchy -the considered algorithms range from dedicated [45] to reduction-based [13,25] approaches (see [19] for a survey). We show that abstract solvers allow for convenient algorithms design resulting in a clear and mathematically precise description. Moreover, formal properties of the algorithms (i.e. correctness) are easily specified by means of related graph properties (i.e. reachability). We then illustrate how abstract solvers allow to highlight in a more clear way similarities and differences among solvin...

show abstract

“…It is worthy to emphasise that Watts-Strogatz and BarabasiAlbert produce undirected graphs: in this work, differently from [5], each edge of the undirected graph is then associated with a direction following a probability distribution, that can be provided as input to AFBenchGen. Finally, the fourth set has been generated using the code provided in Probo [8] by the organisers of ICCMA-15 [20].…”

Section: Experimental Analysismentioning

confidence: 99%

“…We considered all the 15 solvers that took part in the EE-PR track of ICCMA-15 [20]. For the sake of clarity and conciseness, we removed from the analysis single solvers that did not successfully analyse at least one AF or which were always outperformed by another solver.…”

Section: Experimental Analysismentioning

confidence: 99%

On the Combination of Argumentation Solvers into Parallel Portfolios

Vallati

Cerutti

Giacomin

2017

AI 2017: Advances in Artificial Intelligence

Self Cite

View full text Add to dashboard Cite

Abstract. In the light of the increasing interest in efficient algorithms for solving abstract argumentation problems and the pervasive availability of multicore machines, a natural research issue is to combine existing argumentation solvers into parallel portfolios. In this work, we introduce six methodologies for the automatic configuration of parallel portfolios of argumentation solvers for enumerating the preferred extensions of a given framework. In particular, four methodologies aim at combining solvers in static portfolios, while two methodologies are designed for the dynamic configuration of parallel portfolios. Our empirical results demonstrate that the configuration of parallel portfolios is a fruitful way for exploiting multicore machines, and that the presented approaches outperform the state of the art of parallel argumentation solvers.

show abstract

Summary Report of the First International Competition on Computational Models of Argumentation

Cited by 41 publications

References 6 publications

Encoding Argumentation Semantics by Boolean Algebra

Encoding Argumentation Semantics by Boolean Algebra

Abstract solvers for Dung’s argumentation frameworks

On the Combination of Argumentation Solvers into Parallel Portfolios

Contact Info

Product

Resources

About