Computational Models Of Argumentation Research Articles

(Conceptual) explanations in logic

Abstract To explain phenomena in the world is a central human activity and one of the main goals of rational inquiry. There are several types of explanation: one can explain by drawing an analogy, as one can explain by dwelling on the causes (see e.g. see [Woodward (2004, Making Things Happen: A Theory of Causal Explanation. Oxford University Press, Oxford)]. Amongst these different kinds of explanation, in the last decade, philosophers have become receptive to those explanations that explain by providing the reasons (or the grounds) why a statement is true; these explanations are often called conceptual explanations (e.g. see [Betti (2010, Explanation in metaphysics and Bolzano's theory of ground and consequence. Logique et analyse, 211:281316)]). The main aim of the paper is to propose a logical account of conceptual explanations. We will do so by using the resources of proof theory, in particular sequent rules analogous to deep inferences ([e.g. see Brunnler (2004, Deep Inference and Symmetry in Classical Proofs. Logoc Verlag)]). The results we provide not only shed light on conceptual explanations themselves, but also on the role that logic and logical tools might play in the burgeoning field of inquiry concerning explanations. Indeed, we conclude the paper by underlining interesting links between the present research and some other existing works on explanations and logic that have arise in recent years, e.g. see [Arieli et al. (2022, Explainable logic-based argumentation. Computational Models of Argument, 353:3243); Darwiche and Hirth (2023, On the (complete) reasons behind decisions. Journal of Logic Language and Information, 32:6388); Piazza, Pulcini, and Sabatini (2023, Abduction as deductive saturation: a proof-theoretic inquiry. Journal of Philosophical Logic, 52:15751602)]. For here it is for the empirical scientist to know the fact and for the mathematical to know the reason why (our emphasis) [Aristotle (1993, Posterior Analytics. Oxford University Press, Oxford)].

Pygarg: A Python engine for argumentation

Recent advancements in algorithms for abstract argumentation make it possible now to solve reasoning problems even with argumentation frameworks of large size, as demonstrated by the results of the various editions of the International Competition on Computational Models of Argumentation (ICCMA). However, the solvers participating to the competition may be hard to use for non-expert programmers, especially if they need to incorporate these algorithms in their own code instead of simply using the command-line interface. Moreover, some ICCMA solvers focus on the ICCMA tracks, and do not implement algorithms for other problems. In this paper we describe pygarg, a Python implementation of the SAT-based approach used in the argumentation solver CoQuiAAS. Contrary to CoQuiAAS and most of the participants to the various editions of ICCMA, pygarg incorporates all problems that have been considered in the main track of any edition of ICCMA. We show how to easily use pygarg via a command-line interface inspired by ICCMA competitions, and then how it can be used in other Python scripts as a third-party library.

The third and fourth international competitions on computational models of argumentation: Design, results and analysis

The International Competition on Computational Models of Argumentation (ICCMA) focuses on reasoning tasks in abstract argumentation frameworks. Submitted solvers are tested on a selected collection of benchmark instances, including artificially generated argumentation frameworks and some frameworks formalizing real-world problems. This paper presents the novelties introduced in the organization of the Third (2019) and Fourth (2021) editions of the competition. In particular, we proposed new tracks to competitors, one dedicated to dynamic solvers (i.e., solvers that incrementally compute solutions of frameworks obtained by incrementally modifying original ones) in ICCMA’19 and one dedicated to approximate algorithms in ICCMA’21. From the analysis of the results, we noticed that i) dynamic recomputation of solutions leads to significant performance improvements, ii) approximation provides much faster results with satisfactory accuracy, and iii) classical solvers improved with respect to previous editions, thus revealing advancement in state of the art.

Argument strength in probabilistic argumentation based on defeasible rules

It is common for people to remark that a particular argument is a strong (or weak) argument. Having a handle on the relative strengths of arguments can help in deciding on which arguments to consider, which arguments to regard as acceptable, and on which arguments to present to others in a discussion. In computational models of argument, there is a need for a deeper understanding of argument strength. It is a multidimensional problem, and in this paper, we focus on one aspect of argument strength for deductive argumentation based on a defeasible logic. We assume a probability distribution over models of the language and consider how there are various ways to calculate argument strength based on the probabilistic necessity and sufficiency of the premises for the claim, the probabilistic sufficiency of competing premises the claim, and the probabilistic necessity of the premises for competing claims. We provide axioms for characterizing probability-based measures of argument strength, and we investigate four specific probability-based measures.

Summary report for the third international competition on computational models of argumentation

AbstractThe Third International Competition on Computational Models of Argumentation (ICCMA'19) focused on reasoning tasks in abstract argumentation frameworks. Submitted solvers were tested on a selected collection of benchmark instances, including artificially generated argumentation frameworks and some frameworks formalizing real‐world problems. This competition introduced two main novelties over the two previous editions: the first one is the use of the Docker platform for packaging the participating solvers into virtual “light” containers; the second novelty consists of a new track for dynamic frameworks.

ConArgLib: an argumentation library with support to search strategies and parallel search

ABSTRACT We present ConArgLib, a C++ library implemented to help programmers solve some of the most important problems related to extension-based abstract Argumentation. The library is based on ConArg, which exploits Constraint Programming and, in particular, Gecode, a toolkit for developing constraint-based systems and applications. Given a semantics, such problems consist, for example, in enumerating all the extensions, and checking the credulous or sceptical acceptance of an argument passed as parameter. The goal is to let programmers use the library to quickly develop programs on top of it, as, for instance, implementing decision-making procedures based on the strongest arguments, or comparing two frameworks by looking at the differences between their (e.g., stable) semantics. The library features the possibility to use different branching strategies, which we all test and compare on a set of frameworks taken from the International Competition on Computational Models of Argumentation (ICCMA17). Moreover, for some of the tasks, it is possible to perform a parallel search using several workers at the same time: we test the speed-up between using from 1 to 16 threads on a set of ICCMA17 frameworks.

A parametrized ranking-based semantics compatible with persuasion principles

In this work, we question the ability of existing ranking-based semantics to capture persuasion settings, emphasising in particular the phenomena of procatalepsis (the fact that it is often efficient to anticipate the counter-arguments of the audience) and of fading (the fact that long lines of argumentation become ineffective). Some widely accepted principles of ranking-based semantics (like Void Precedence) are incompatible with a faithful treatment of these phenomena, which means that no existing ranking-based semantics can capture these two principles together. This motivates us to introduce a new parametrized ranking-based semantics based on the notion of propagation which extends the existing propagation semantics (In Proceedings of the 6th International Conference on Computational Models of Argument (COMMA’16) (2016) 139–150) by adding an additional parameter allowing us to gradually decrease the impact of arguments when the length of the path between two arguments increases. We show that this parameter gives the possibility of choosing if one wants to satisfy the property Void Precedence or not (and then capture procatalepsis) and to control the scope of the impact of the arguments (and then to capture fading principle). We also propose an experiment to show that the new semantics remains stable when this parameter varies and an axiomatic evaluation to compare it with existing ranking-based semantics in the literature.

Enhancing Statement Evaluation in Argumentation via Multi-labelling Systems

In computational models of argumentation, the justification of statements has drawn less attention than the construction and justification of arguments. Significant losses of sensitivity or expressibility on statement statuses can be incurred by otherwise appealing formalisms. In order to reappraise statement statuses and, more generally, to support a uniform modelling of different phases of the argumentation process we introduce multi-labelling systems, a generic formalism devoted to represent reasoning processes consisting of a sequence of labelling stages. In the argumentation context, two families of multi-labelling systens, called argument-focused and statement-focused approach are identified and compared. Then they are shown to be able to encompass several prominent literature proposals as special cases, thereby enabling a systematic comparison evidencing their merits and limits. Further, we show that the proposed model supports tunability of statement justification by specifying a few alternative statement justification labellings, and we illustrate how they can be seamlessly integrated into different formalisms.

Design and results of the Second International Competition on Computational Models of Argumentation

Argumentation is a major topic in the study of Artificial Intelligence. Since the first edition in 2015, advancements in solving (abstract) argumentation frameworks are assessed in competition events, similar to other closely related problem solving technologies. In this paper, we report about the design and results of the Second International Competition on Computational Models of Argumentation, which has been jointly organized by TU Dresden (Germany), TU Wien (Austria), and the University of Genova (Italy), in affiliation with the 2017 International Workshop on Theory and Applications of Formal Argumentation. This second edition maintains some of the design choices made in the first event, e.g. the I/O formats, the basic reasoning problems, and the organization into tasks and tracks. At the same time, it introduces significant novelties, e.g. three additional prominent semantics, and an instance selection stage for classifying instances according to their empirical hardness.

The Agile Robotics for Industrial Automation Competition

The Agile Robotics for Industrial Automation Competition (ARIAC) is an annual simulation‐based competition initiated in 2017. The competition challenges teams to design industrial robotic system control code to function in a dynamic environment. Each team's system is faced with challenges such as dropped parts, which it must address, without operator intervention, while continuing to function.

Warsaw Argumentation Week (Waw 2018) Organised by the Polish School of Argumentation and Our Colleagues from Germany and the UK, 6th-16th September 2018

Abstract In September 2018, the ArgDiaP association, along with colleagues from Germany and the UK, organised one of the longest and most interdisciplinary series of events ever dedicated to argumentation - Warsaw Argumentation Week, WAW 2018. The eleven-day ‘week’ featured a five day graduate school on computational and linguistic perspectives on argumentation (3rd SSA school); five workshops: on systems and algorithms for formal argumentation (2nd SAFA), argumentation in relation to society (1st ArgSoc), philosophical approaches to argumentation (1st ArgPhil), legal argumentation (2ndMET-ARG) and argumentation in rhetoric (1st MET-RhET); and two conferences: on computational models of argumentation (7th COMMA conference) and on argumentation and corpus linguistics (16th ArgDiaP conference). WAW hosted twelve tutorials and eight invited talks as well as welcoming over 130 participants. All the conferences and workshops publish pre- or post-proceedings in the top journals and book series in the field.

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.

The first international competition on computational models of argumentation: Results and analysis

We report on the First International Competition on Computational Models of Argumentation (ICCMA'15) which took place in the first half of 2015 and focused on reasoning tasks in abstract argumentation frameworks. Performance of submitted solvers was evaluated on four computational problems wrt. four different semantics relating to the verification of the acceptance status of arguments, and computing jointly acceptable sets of arguments. In this paper, we describe the technical setup of the competition, and give an overview on the submitted solvers. Moreover, we report on the results and discuss our findings.

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.

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

We review the First International Competition on Computational Models of Argumentation (ICCMA'15). The competition evaluated submitted solvers' performance on four different computational tasks related to solving abstract argumentation frameworks. Each task evaluated solvers in ways that pushed the edge of existing performance by introducing new challenges. Despite being the first competition in this area, the high number of competitors entered, and differences in results, suggest that the competition will help shape the landscape of ongoing developments in argumentation theory solvers.

Recommendations to support interaction with broadcast debates: a study on older adults’ interaction with The Moral Maze

Current methods to capture, analyse and present the audience participation of broadcast events are increasingly carried out using social media. Uptake of such technology tools has so far been poor amongst older adults, and it has the worrying effect of excluding the demographic from participation. Our work explores whether a common desire to interact with debates can be tapped with technology with a very low barrier to entry, to both support better engagement with broadcast debates and encourage greater use of social media. This paper describes experiments where older adults interact with a BBC radio debate programme: The Moral Maze. As a result, we obtained common interaction patterns which then are used to define recommendations for software-supported interaction with debates based on theories of argumentation. Our goal is to combine research on computational models of argument and user-driven research on human-centred computing in a project with the potential for high-profile impact in addressing older adults inclusion in the digital economy.

A computational model of argumentation in agreement negotiation processes

The paper describes a computational model that we have implemented in an experimental dialogue system (DS). Communication in a natural language between two participants A and B is considered, where A has a communicative goal that his/her partner B wi

Arguing over Goals for Negotiation: Adopting an Assumption-Based Argumentation Decision Support System

Computational models of argumentation has been put forward as a promising approach to support decision making. In this context several recent works have proposed argumentation-based frameworks for decision making. In this paper we describe an application based on an argumentation-based mechanism for decision-making to concede. Adopting the assumption-based approach of argumentation, we propose an argumentation framework in which preferences are attached to goals. Arguments are defined as tree-like structures. Our framework is equipped with a computational counterpart for solving a decision problem, modeling the intuition that high-ranked goals are preferred to low-ranked goals which can be withdrawn. In this way, our framework suggests some decisions and provides an interactive and intelligible explanation of this choice. Our implementation, called MARGO, has been used for service selection within the ArguGRID project. We illustrate our approach with an industrial application, and illustrate the operation of the system with a running example.

A System for Simulating Human Argumentation: Test Results Compared With a Realistic Institutional Setting

A prototype system is described that simulates a transcript of a business meeting based on a computational model of argumentation using the distinction between premises, conclusions, and warrants. The argumentation in the dialogue is represented as a directional weighted graph. An algorithm for calculating the strength of each conclusion is described, and the results are shown for the business meeting transcript. These results are compared with perceptions of the strength of the arguments in the meeting by a group of management graduates.

Incorporating rhetorical and plausible reasoning in a system for simulating argumentation

Abstract The article introduces argumentation theory, some examples of computational models of argumentation, some application examples, considers the significance and problems of argumentation systems, and outlines the significance and difficulties of the field. Also, the article describes a system which used rhetorical reasoning rules such as fairness, reciprocity, and deterrence which was used to simulate the text of a debate. The text was modelled using modern argumentation theory, and this model was used to build the system. The article discusses the system with regard to several aspects: its ability to deal with meaningful contradiction such as claim X supporting claim Y, yet claim Y attacking claim X; recursive arguments; inconsistency maintenance; expressiveness; encapsulation, the use of definitions as the basis for rules, and making generalisations using taxonomies. The article concludes with a discussion of domain dependence, rule plausibility, and some comparisons with formal logic.