On the Expressive Power of Assumption-Based Argumentation

LOGICS IN ARTIFICIAL INTELLIGENCE, JELIA 2023(2023)

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摘要
The expressiveness of any given formalism lays the theoretical foundation for more specialized topics such as investigating dynamic reasoning environments. The modeling capabilities of the formalism under investigation yield immediate (im)possibility results in such contexts. In this paper we investigate the expressiveness of assumption-based argumentation (ABA), one of the major structured argumentation formalisms. In particular, we examine so-called signatures, i.e., sets of extensions that can be realized under a given semantics. We characterize the signatures of common ABA semantics for flat, finite frameworks with and without preferences. We also give several results regarding conclusion-based semantics for ABA.
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