A Plausibility Semantics for Abstract Argumentation Frameworks
This work addresses foundational issues in computational argumentation for AI and logic communities, but appears incremental as it builds on existing default reasoning concepts.
The paper tackles the problem of defining extension semantics for abstract argumentation frameworks by proposing a ranking-measure-based approach derived from default knowledge bases and ranking construction semantics, resulting in the well-justified JZ-extension semantics that diverges from traditional methods.
We propose and investigate a simple ranking-measure-based extension semantics for abstract argumentation frameworks based on their generic instantiation by default knowledge bases and the ranking construction semantics for default reasoning. In this context, we consider the path from structured to logical to shallow semantic instantiations. The resulting well-justified JZ-extension semantics diverges from more traditional approaches.