Argument & Computation - Volume Pre-press, issue Pre-press

Authors: Caminada, Martin | König, Matthias | Rapberger, Anna | Ulbricht, Markus

Article Type: Research Article

Abstract: In the current paper we re-examine the concepts of attack semantics and collective attacks in abstract argumentation, and examine how these concepts interact with each other. For this, we systematically map the space of possibilities. Starting with standard argumentation frameworks (which consist of a directed graph with nodes and arrows) we briefly state both node semantics and arrow semantics (the latter a.k.a. attack semantics) in both their extensions-based form and labellings-based form. We then proceed with SETAFs (which consist of a directed hypergraph of nodes and arrows, to take into account the notion of collective attacks) and state both node …semantics and arrow semantics, in both their extensions-based and labellings-based form. We then show equivalence between the extensions-based and labellings-based form, for node semantics and arrow semantics of AFs, as well as for node semantics and arrow semantics of SETAFs. Moreover, we show equivalence between node semantics and arrow semantics for AFs, and equivalence between node semantics and arrow semantics for SETAFs (with the notable exception of semi-stable). We also provide a novel way of converting a SETAF to an AF such that semantics are preserved, without the use of any “meta arguments”. Although the main part of our work is on the level of abstract argumentation, we do provide an application of our theory on the instantiated level. More specifically, we show that the classical characterisation of Assumption-Based Argumentation (ABA) can be seen as an instantiation based on a SETAF, whereas the contemporary characterisation of ABA can be seen as an instantiation based on a standard AF. Our theory of how to convert a SETAF to an AF can then be used to account for both the similarities and the differences between the classical and contemporary characterisations of ABA. Most prominently, our theory is able to explain the semantic mismatch for semi-stable semantics that arises in the ABA instantiation process. Show more

Keywords: Abstract argumentation, assumption-based argumentation, attack semantics, collective attacks

DOI: 10.3233/AAC-230011

Citation: Argument & Computation, vol. Pre-press, no. Pre-press, pp. 1-77, 2024

Authors: Castagna, Federico | McBurney, Peter | Parsons, Simon

Article Type: Research Article

Abstract: Advancements and deployments of AI-based systems, especially Deep Learning-driven generative language models, have accomplished impressive results over the past few years. Nevertheless, these remarkable achievements are intertwined with a related fear that such technologies might lead to a general relinquishing of our lives’s control to AIs. This concern, which also motivates the increasing interest in the eXplainable Artificial Intelligence (XAI) research field, is mostly caused by the opacity of the output of deep learning systems and the way that it is generated, which is largely obscure to laypeople. A dialectical interaction with such systems may enhance the users’ understanding and …build a more robust trust towards AI. Commonly employed as specific formalisms for modelling intra-agent communications, dialogue games prove to be useful tools to rely upon when dealing with user’s explanation needs. The literature already offers some dialectical protocols that expressly handle explanations and their delivery. This paper fully formalises the novel Explanation–Question–Response (EQR) dialogue and its properties, whose main purpose is to provide satisfactory information (i.e., justified according to argumentative semantics) whilst ensuring a simplified protocol, in comparison with other existing approaches, for humans and artificial agents. Show more

Keywords: Explainable AI, dialogue games, computational argumentation, dialogue protocols, large language models

DOI: 10.3233/AAC-230015

Citation: Argument & Computation, vol. Pre-press, no. Pre-press, pp. 1-23, 2024

Authors: Bistarelli, Stefano | Kotthoff, Lars | Lagniez, Jean-Marie | Lonca, Emmanuel | Mailly, Jean-Guy | Rossit, Julien | Santini, Francesco | Taticchi, Carlo

Article Type: Research Article

Abstract: 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. Show more

Keywords: Argumentation, semantics, solver, dynamic framework

DOI: 10.3233/AAC-230013

Citation: Argument & Computation, vol. Pre-press, no. Pre-press, pp. 1-73, 2024

Authors: Bezou Vrakatseli, Elfia | Prakken, Henry | Janssen, Christian P.

Article Type: Research Article

Abstract: This paper investigates whether empirical findings on how humans evaluate arguments in reinstatement cases support the ‘fewer attackers is better’ principle, incorporated in many current gradual notions of argument acceptability. Through three variations of an experiment, we find that (1) earlier findings that reinstated arguments are rated lower than when presented alone are replicated, (2) ratings at the reinstated stage are similar if all arguments are presented at once, compared to sequentially, and (3) ratings are overall higher if participants are provided with the relevant theory, while still instantiating imperfect reinstatement. We conclude that these findings could at best support …a more specific principle ‘being unattacked is better than attacked’, but alternative explanations cannot yet be ruled out. More generally, we highlight the danger that experimenters in reasoning experiments interpret examples differently from humans. Finally, we argue that more justification is needed on why, and how, empirical findings on how humans argue can be relevant for normative models of argumentation. Show more

Keywords: Empirical evaluation, simple reinstatement, imperfect reinstatement, suspension of disbelief, graded acceptability

DOI: 10.3233/AAC-230016

Citation: Argument & Computation, vol. Pre-press, no. Pre-press, pp. 1-25, 2024

Authors: Dung, Phan Minh | Thang, Phan Minh | Pooksook, Jiraporn

Article Type: Research Article

Abstract: Dialectical proof procedures in assumption-based argumentation are in general sound but not complete with respect to both the credulous and skeptical semantics (due to non-terminating loops). This raises the question of whether we could describe exactly what such procedures compute. In a previous paper, we introduce infinite arguments to represent possibly non-terminating computations and present dialectical proof procedures that are both sound and complete with respect to the credulous semantics of assumption-based argumentation with infinite arguments. In this paper, we study whether and under what conditions dialectical proof procedures are both sound and complete with respect to the …grounded semantics of assumption-based argumentation with infinite arguments. We introduce the class of ω -grounded and finitary-defensible argumentation frameworks and show that finitary assumption-based argumentation is ω -grounded and finitary-defensible. We then present dialectical procedures that are sound and complete wrt finitary assumption-based argumentation. Show more

Keywords: Dialectical proof procedure, infinite argument, grounded semantics, soundness and completeness

DOI: 10.3233/AAC-230009

Citation: Argument & Computation, vol. Pre-press, no. Pre-press, pp. 1-45, 2024

Authors: Caminada, Martin | Harikrishnan, Sri

Article Type: Research Article

Abstract: Much like admissibility is the key concept underlying preferred semantics, strong admissibility is the key concept underlying grounded semantics, as membership of a strongly admissible set is sufficient to show membership of the grounded extension. As such, strongly admissible sets and labellings can be used as an explanation of membership of the grounded extension, as is for instance done in some of the proof procedures for grounded semantics. In the current paper, we present two polynomial algorithms for constructing relatively small strongly admissible labellings, with associated min–max numberings, for a particular argument. These labellings can be used as relatively small …explanations for the argument’s membership of the grounded extension. Although our algorithms are not guaranteed to yield an absolute minimal strongly admissible labelling for the argument (as doing so would have implied an exponential complexity), our best performing algorithm yields results that are only marginally larger. Moreover, the runtime of this algorithm is an order of magnitude smaller than that of the existing approach for computing an absolute minimal strongly admissible labelling for a particular argument. As such, we believe that our algorithms can be of practical value in situations where the aim is to construct a minimal or near-minimal strongly admissible labelling in a time-efficient way. Show more

Keywords: Abstract argumentation, strong admissibility, algorithms

DOI: 10.3233/AAC-230012

Citation: Argument & Computation, vol. Pre-press, no. Pre-press, pp. 1-31, 2024

Authors: Rocha, Gil | Lopes Cardoso, Henrique | Belouadi, Jonas | Eger, Steffen

Article Type: Research Article

Abstract: Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has received wide attention in various discourse parsing tasks, from which it is well-known that discourse markers are strong indicators of discourse relations. To improve the robustness of Argument Mining systems across different genres, we propose to automatically augment a given text with discourse markers such that all relations are explicitly signaled. Our analysis unveils that popular language models taken out-of-the-box fail on this task; however, …when fine-tuned on a new heterogeneous dataset that we construct (including synthetic and real examples), they perform considerably better. We demonstrate the impact of our approach on an Argument Mining downstream task, evaluated on different corpora, showing that language models can be trained to automatically fill in discourse markers across different corpora, improving the performance of a downstream model in some, but not all, cases. Our proposed approach can further be employed as an assistant tool for better discourse understanding. Show more

Keywords: Computational linguistics, machine learning, language models, discourse analysis, argument mining

DOI: 10.3233/AAC-230008

Citation: Argument & Computation, vol. Pre-press, no. Pre-press, pp. 1-41, 2024

Authors: Mailly, Jean-Guy

Article Type: Research Article

Abstract: 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. Show more

Keywords: Abstract argumentation, SAT-based solver, Python software

DOI: 10.3233/AAC-230019

Citation: Argument & Computation, vol. Pre-press, no. Pre-press, pp. 1-7, 2024

Authors: Marji, Zaid | Licato, John

Article Type: Research Article

Abstract: In natural language understanding, a crucial goal is correctly interpreting open-textured phrases. In practice, disagreements over the meanings of open-textured phrases are often resolved through the generation and evaluation of interpretive arguments , arguments designed to support or attack a specific interpretation of an expression within a document. In this paper, we discuss some of our work towards the goal of automatically generating and evaluating interpretive arguments. We have curated a set of rules from the code of ethics of various professional organizations and a set of associated scenarios that are ambiguous with respect to some open-textured phrase within the …rule. We collected and evaluated arguments from both human annotators and state-of-the-art generative language models in order to determine the relative quality and persuasiveness of both sets of arguments. Finally, we performed a Turing test-inspired study in order to assess whether human annotators can tell the difference between human arguments and machine-generated arguments. The results show that machine-generated arguments, when prompted a certain way, can be consistently rated as more convincing than human-generated arguments, and to the untrained eye, the machine-generated arguments can convincingly sound human-like. Show more

Keywords: Interpretive arguments, persuasion, large language models, generative language models

DOI: 10.3233/AAC-230014

Citation: Argument & Computation, vol. Pre-press, no. Pre-press, pp. 1-51, 2024