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

ANALYSIS OF THE EFFECTIVENESS OF ARGUMENTATION LEARNING MODELS FOR INCREASING STUDENTS ARGUMENTATION SKILLS BASED ON SCORING MATRIX LEVELS OF TOULMINS ARGUMENTATION PATTERN (TAP) IN PHYSICS LEARNING

This study aims to determine the effectiveness of learning models in improving students argumentation skills. This effectiveness is in the form of increasing the level of argumentation of students from before applying the learning model until after the learning model is applied. The type of research used is library research, that is research in which data or research objects are obtained through various library information such as journals, books, encyclopedias, and similar literature. The data source used by this research is secondary data. This research data analysis method is a descriptive analysis method, which is the decomposition of data obtained regularly and then given an understanding and explanation so that the reader can understand the contents of the data obtained properly. Based on the results of the study, it was found that the average argumentation skill of students using the scoring matrix Toulmins Argumentation Pattern before applying the learning model was at level 1-2. After applying learning and re-measuring the skill of argumentation shows level 3-4 although in one learning model still shows level 2. Two learning models are best to be applied to improving students argumentation skills. First the inquiry model with the Argument Based Science Inquiry (ABSI) learning model with an increase of 2 levels after learning is applied with a high n-gain value category. Second, Argument-Driven Inquiry (ADI) with an increase of 2 levels after applying learning with a moderate n-gain value category. Both of these models can improve students argumentation skill to level 4 where after learning the students can formulate arguments accompanied by a conditional rebuttal and the rebuttal begins to be seen

Empirical Evaluation of Abstract Argumentation: Supporting the Need for Bipolar and Probabilistic Approaches

In dialogical argumentation it is often assumed that the involved parties always correctly identify the intended statements posited by each other, realize all of the associated relations, conform to the three acceptability states (accepted, rejected, undecided), adjust their views when new and correct information comes in, and that a framework handling only attack relations is sufficient to represent their opinions. Although it is natural to make these assumptions as a starting point for further research, removing them or even acknowledging that such removal should happen is more challenging for some of these concepts than for others. Probabilistic argumentation is one of the approaches that can be harnessed for more accurate user modelling. The epistemic approach allows us to represent how much a given argument is believed by a given person, offering us the possibility to express more than just three agreement states. It is equipped with a wide range of postulates, including those that do not make any restrictions concerning how initial arguments should be viewed, thus potentially being more adequate for handling beliefs of the people that have not fully disclosed their opinions in comparison to Dung's semantics. The constellation approach can be used to represent the views of different people concerning the structure of the framework we are dealing with, including cases in which not all relations are acknowledged or when they are seen differently than intended. Finally, bipolar argumentation frameworks can be used to express both positive and negative relations between arguments. In this paper we describe the results of an experiment in which participants judged dialogues in terms of agreement and structure. We compare our findings with the aforementioned assumptions as well as with the constellation and epistemic approaches to probabilistic argumentation and bipolar argumentation

About the Infinite Repetition of Histories in Space

This paper analyzes two different proposals, one by Ellis and Brundrit, based on classical relativistic cosmology, the other by Garriga and Vilenkin, based on the DH interpretation of quantum mechanics, both of which conclude that, in an infinite universe, planets and living beings must be repeated an infinite number of times. We point to some possible shortcomings in the arguments of these authors. We conclude that the idea of an infinite repetition of histories in space cannot be considered strictly speaking a consequence of current physics and cosmology. Such ideas should be seen rather as examples of {\guillemotleft}ironic science{\guillemotright} in the terminology of John Horgan.Comment: 14 pages, no figures. Accepted for publication in slightly different form at THEORIA (http://www.ehu.es/ojs/index.php/THEORIA

Abstract Argumentation / Persuasion / Dynamics

The act of persuasion, a key component in rhetoric argumentation, may be viewed as a dynamics modifier. We extend Dung's frameworks with acts of persuasion among agents, and consider interactions among attack, persuasion and defence that have been largely unheeded so far. We characterise basic notions of admissibilities in this framework, and show a way of enriching them through, effectively, CTL (computation tree logic) encoding, which also permits importation of the theoretical results known to the logic into our argumentation frameworks. Our aim is to complement the growing interest in coordination of static and dynamic argumentation.Comment: Arisaka R., Satoh K. (2018) Abstract Argumentation / Persuasion / Dynamics. In: Miller T., Oren N., Sakurai Y., Noda I., Savarimuthu B., Cao Son T. (eds) PRIMA 2018: Principles and Practice of Multi-Agent Systems. PRIMA 2018. Lecture Notes in Computer Science, vol 11224. Springer, Cha