Properties of ABA+ for Non-Monotonic Reasoning

We investigate properties of ABA+, a formalism that extends the well studied structured argumentation formalism Assumption-Based Argumentation (ABA) with a preference handling mechanism. In particular, we establish desirable properties that ABA+ semantics exhibit. These pave way to the satisfaction by ABA+ of some (arguably) desirable principles of preference handling in argumentation and nonmonotonic reasoning, as well as non-monotonic inference properties of ABA+ under various semantics.Comment: This is a revised version of the paper presented at the worksho

Argumentation update in YALLA (Yet Another Logic Language for Argumentation)

International audienceThis article proposes a complete framework for handling the dynamics of an abstract argumentation system. This frame can encompass several belief bases under the form of several argumentation systems, more precisely it is possible to express and study how an agent who has her own argumentation system can interact on a target argumentation system (that may represent a state of knowledge at a given stage of a debate). The two argumentation systems are defined inside a reference argumentation system called the universe which constitutes a kind of “common language”. This paper establishes three main results. First, we show that change in argumentation in such a framework can be seen as a particular case of belief update. Second, we have introduced a new logical language called YALLA in which the structure of an argumentation system can be encoded, enabling to express all the basic notions of argumentation theory (defense, conflict-freeness, extensions) by formulae of YALLA. Third, due to previous works about dynamics in argumentation we have been in position to provide a set of new properties that are specific for argumentation update

Advancing the Boundaries of Formal Argumentation: Reflections on the AI3 2021 Special Issue

This article reflects on the Special Issue based on invited papers from the 5th Workshop on Advances in Argumentation in Artificial Intelligence (AI3 2021), showcasing the latest advancements in the field made by the Italian community on argumentation, as well as other researchers worldwide. This Special Issue highlights the importance of advancing logical-based AI approaches, such as formal argumentation, in the continuously expanding landscape of Artificial In- telligence. Papers in this Special Issue cover a diverse range of topics, including argument game-based proof theories, analysis of legal cases, decomposability in abstract argumentation, meta-argumentation approaches, explanations for model outputs using causal models, representation of natural argumentative discourse, and Paraconsistent Weak Kleene logic-based belief revision. By em- phasizing these innovative research contributions, this article underscores the need for continued progress in the field of Formal Argumentation to complement and enhance the ongoing developments in AI

Liberalism and the Moral Significance of Individualism: A Deweyan View

A liberalism which scorns all individualism is fundamentally misguided. This is the chief thesis of this paper. To argue for it, I look closely at some key concepts. The concepts of morislity and individualism are crucial. I emphasize Dewey on the "individuality of the mind" and a Deweyan discussion of language, communication, and community. The thesis links individualism and liberalism, and since appeals to liberalism have broader appeal in the present context of discussions, I start with consideration of liberalism. The aim is to dispute overly restrictive conceptions and explore a broader perspective. To bring the argument to a close, attention turns first to Dewey on value inquiry, to Dewey's "democratic individualism" (cf. Dewey 1939, 179), and to the concept of moral community. Disputing the acquisitiveness of utilitarian influences in classical liberalism, a Deweyan argument from the nature of moral community supports re-emphasis on individualism in contemporary liberal thought

A Computational-Hermeneutic Approach for Conceptual Explicitation

We present a computer-supported approach for the logical analysis and conceptual explicitation of argumentative discourse. Computational hermeneutics harnesses recent progresses in automated reasoning for higher-order logics and aims at formalizing natural-language argumentative discourse using flexible combinations of expressive non-classical logics. In doing so, it allows us to render explicit the tacit conceptualizations implicit in argumentative discursive practices. Our approach operates on networks of structured arguments and is iterative and two-layered. At one layer we search for logically correct formalizations for each of the individual arguments. At the next layer we select among those correct formalizations the ones which honor the argument's dialectic role, i.e. attacking or supporting other arguments as intended. We operate at these two layers in parallel and continuously rate sentences' formalizations by using, primarily, inferential adequacy criteria. An interpretive, logical theory will thus gradually evolve. This theory is composed of meaning postulates serving as explications for concepts playing a role in the analyzed arguments. Such a recursive, iterative approach to interpretation does justice to the inherent circularity of understanding: the whole is understood compositionally on the basis of its parts, while each part is understood only in the context of the whole (hermeneutic circle). We summarily discuss previous work on exemplary applications of human-in-the-loop computational hermeneutics in metaphysical discourse. We also discuss some of the main challenges involved in fully-automating our approach. By sketching some design ideas and reviewing relevant technologies, we argue for the technological feasibility of a highly-automated computational hermeneutics.Comment: 29 pages, 9 figures, to appear in A. Nepomuceno, L. Magnani, F. Salguero, C. Bar\'es, M. Fontaine (eds.), Model-Based Reasoning in Science and Technology. Inferential Models for Logic, Language, Cognition and Computation, Series "Sapere", Springe

Non-monotonic inference properties for assumption-based argumentation

Cumulative Transitivity and Cautious Monotonicity are widely considered as important properties of non-monotonic inference and equally as regards to information change. We propose three novel formulations of each of these properties for Assumption-Based Argumentation (ABA)-an established structured argumentation formalism, and investigate these properties under a variety of ABA semantics

Ontology evolution: a process-centric survey

Ontology evolution aims at maintaining an ontology up to date with respect to changes in the domain that it models or novel requirements of information systems that it enables. The recent industrial adoption of Semantic Web techniques, which rely on ontologies, has led to the increased importance of the ontology evolution research. Typical approaches to ontology evolution are designed as multiple-stage processes combining techniques from a variety of fields (e.g., natural language processing and reasoning). However, the few existing surveys on this topic lack an in-depth analysis of the various stages of the ontology evolution process. This survey extends the literature by adopting a process-centric view of ontology evolution. Accordingly, we first provide an overall process model synthesized from an overview of the existing models in the literature. Then we survey the major approaches to each of the steps in this process and conclude on future challenges for techniques aiming to solve that particular stage

Hypotheses and their dynamics in legal argumentation

We investigate some legal interpretation techniques from the viewpoint of the Argentinian jurisprudence. This allows the proposal of a logical framework –from a computer science perspective– for modeling such specific reasoning techniques towards an appropriate construction of legal arguments. Afterwards, we study the usage of assumptions towards construction of hypotheses. This is proposed in the dynamic context of legal procedures, where the referred argumentation framework evolves as part of the investigation instance prior to the trial. We propose belief revision operators to handle such dynamics, preserving a coherent behavior with regards to the legal interpretation used. Abduction is finally proposed to construct systematic hypothesization, with the objective to bring semi-automatic recommendations to push forward the investigation of a legal case