Abstract
Argumentation can be viewed as a process of generating explanations. However, existing argumentation semantics are developed for identifying acceptable arguments within a set, rather than giving concrete justifications for them. In this work, we propose a new argumentation semantics, related admissibility, designed for giving explanations to arguments in both Abstract Argumentation and Assumption-based Argumentation. We identify different types of explanations defined in terms of the new semantics. We also give a correct computational counterpart for explanations using dispute forests.
Cite
CITATION STYLE
Fan, X., & Toni, F. (2015). On computing explanations in argumentation. In Proceedings of the National Conference on Artificial Intelligence (Vol. 2, pp. 1496–1502). AI Access Foundation. https://doi.org/10.1609/aaai.v29i1.9420
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