We address the issue of forgetting in assumption-based argumentation (ABA). Forgetting is
driven by the goal to remove certain elements from a knowledge base, while preserving the …

Abstract Reasoning under incomplete information is an important research direction in AI
argumentation. Most computational advances in this direction have so far focused on …

This paper proposes a structured variant in ASPIC+ of the notion of expansions of abstract
argumentation frameworks. The purpose of this is threefold: studying what it takes to …

The expressiveness of any given formalism lays the theoretical foundation for more
specialized topics such as investigating dynamic reasoning environments. The modeling …

Dung's abstract argumentation frameworks (AFs) are a key formalism in AI research
nowadays. Claims are an inherent part of each argument; they substantially determine the …

Assumption-based Argumentation (ABA) is a well-known structured argumentation
formalism, whereby arguments and attacks between them are drawn from rules, defeasible …

This paper presents a formal model of dialectical argument strength in terms of the number
of ways in which an argument can be successfully attacked in expansions of an 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 …

AI has become pervasive in recent years, but state-of-the-art approaches predominantly
neglect the need for AI systems to be contestable. Instead, contestability is advocated by AI …

Computational argumentation is a well-established area within Artificial Intelligence (AI)[3,
15]. Specifically within multi-agent systems, argumentation was applied in several directions …