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Dov Gabbay

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9 papers
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9

FLAP Journal 2026 Journal Article

Spaces of Argumentation and their Interaction: The Role of Media in Public Discussion. Two Case Studies

  • Dov Gabbay
  • Gabriella Pigozzi
  • Juliette Rouchier

This article analyses how distinct argumentation spaces – media, law, and science – interact and collide, using Liebeck v. McDonald’s as a legal case study and the hydroxychloroquine COVID-19 debate as a case of scientific dispute. Building on these two case studies, this analysis shows that arguments that in- tervene in many public debates originate from and move across different spaces, which employ different criteria, rules of evidence, and modes of reasoning for evaluating arguments. Furthermore, our study shows media-driven simplifica- tion, reframing, and truncation of nuanced expert exchanges, producing polar- ized public perceptions and policy consequences. The key features we identified include sliding arguments, repetition-driven strength (clones), shifting proof standards, hedgehog arguments, and zombie information, with implications for formalizing real-world argumentative dynamics and improving cross-space dia- logue. We thank the anonymous reviewers for their valuable comments and suggestions. In particular, we are grateful to Thierry Simonelli for his extensive observations and thoughtful criticisms of the manuscript.

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JAIR Journal 2025 Journal Article

Forgetting in Abstract Argumentation: Limits and Possibilities

  • Ringo Baumann
  • Matti Berthold
  • Dov Gabbay
  • Odinaldo Rodrigues

The topic of forgetting, which loosely speaking means losing, removing, or even hiding some variables, propositions, or formulas, has been extensively studied in the field of knowledge representation and reasoning for many major formalisms. In this article, we convey this topic to the highly active field of abstract argumentation. We provide an in-depth analysis of desirable syntactical and/or semantical properties of possible forgetting operators. In doing so, we included well-known logic programming conditions, such as strong persistence or strong invariance. Further, we argue that although abstract argumentation and logic programming are closely related, it is not possible to reduce forgetting in abstract argumentation to forgetting in logic programming in a straightforward manner. The analysis of desiderata, adapted to the specifics of abstract argumentation, includes implications among them, individual and collective satisfiability, and identifying inherent limits for a set of prominent semantics. Finally, we conduct a case study on stable semantics incorporating concrete forgetting operators.

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JAIR Journal 2025 Journal Article

From Knowledge to Action: Logics of Permitted and Obligatory Announcements

  • Xu Li
  • Guillaume Aucher
  • Dov Gabbay
  • Réka Markovich

We formalize the notions of “permitted and obligatory announcements” in the context of information security, such as privacy policy compliance. In a sender-receiver setting, we define the sender’s permitted and obligatory announcements in terms of the receiver’s ideal epistemic states (i.e., the epistemic states that comply with the given security policies). We propose two logics, LPOA and DLPOA, to reason about permitted and obligatory announcements in static and dynamic contexts, respectively. These two logics are completely axiomatized, and we also study generalizations in which the receiver’s knowledge is characterized by non-S5 logics. Our paper makes two main contributions to the formalization of permitted and obligatory announcements: First, we clarify the interplay between the sender’s permitted and obligatory announcements and the receiver’s knowledge. Second, we distinguish between weakly and strongly permitted announcements.

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KR Conference 2022 Conference Paper

Dynamic Deontic Logic for Permitted Announcements

  • Xu Li
  • Dov Gabbay
  • Réka Markovich

In this paper, we introduce and study a dynamic deontic logic for permitted announcements. In our logic framework, it is permitted to announce something if announcing it would not lead to forbidden knowledge. It is shown that the logic is not compact, and we propose a sound and weakly complete Hilbert-style axiomatisation. We also study the computational complexity of the model checking problem and the decidability of the satisfiability problem. Finally, we introduce a neighbourhood semantics with a strongly complete axiomatisation.

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AAAI Conference 2020 Conference Paper

Forgetting an Argument

  • Ringo Baumann
  • Dov Gabbay
  • Odinaldo Rodrigues

The notion of forgetting, as considered in the famous paper by Lin and Reiter in 1994 has been extensively studied in classical logic and more recently, in non-monotonic formalisms like logic programming. In this paper, we convey the idea of forgetting to another major AI formalism, namely Dungstyle argumentation frameworks. Our approach is axiomaticdriven and not limited to any specific semantics: we propose semantical and syntactical desiderata encoding different criteria for what forgetting an argument might mean; analyze how these criteria relate to each other; and check whether the criteria can be satisfied in general. The analysis is done for a number of widely used argumentation semantics. Our investigation shows that almost all desiderata are individually satis- fiable. However, combinations of semantical and/or syntactical conditions reveal a much more interesting landscape. For instance, we found that the ad hoc approach to forgetting an argument, i. e. , by the syntactical removal of the argument and all of its associated attacks, is too restrictive and only compatible with the two weakest semantical desiderata. Amongst the several interesting combinations identified, we showed that one satisfies a notion of minimal change and presented an algorithm that given an AF F and argument x, constructs a suitable AF G satisfying the conditions in the combination.

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NeurIPS Conference 2005 Conference Paper

A Connectionist Model for Constructive Modal Reasoning

  • Artur Garcez
  • Luis Lamb
  • Dov Gabbay

We present a new connectionist model for constructive, intuitionistic modal reasoning. We use ensembles of neural networks to represent in- tuitionistic modal theories, and show that for each intuitionistic modal program there exists a corresponding neural network ensemble that com- putes the program. This provides a massively parallel model for intu- itionistic modal reasoning, and sets the scene for integrated reasoning, knowledge representation, and learning of intuitionistic theories in neural networks, since the networks in the ensemble can be trained by examples using standard neural learning algorithms.

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