In this paper, we tackle the problem of efficiently recomputing the skeptical acceptance of dynamic argumentation frameworks under the well-known preferred semantics. We discuss an incremental algorithmic solution whose main idea is that of exploiting the initial knowledge (including the update to perform) in order to identify a potentially small portion of the argumentation framework. Such a portion is sufficient to compute the skeptical preferred acceptance of a goal argument w.r.t. the whole updated framework. We also discuss on how similar ideas extend to more general argumentation frameworks.

Incremental Skeptical Preferred Acceptance in Dynamic Argumentation Frameworks

Alfano G.;Greco S.
2021

Abstract

In this paper, we tackle the problem of efficiently recomputing the skeptical acceptance of dynamic argumentation frameworks under the well-known preferred semantics. We discuss an incremental algorithmic solution whose main idea is that of exploiting the initial knowledge (including the update to perform) in order to identify a potentially small portion of the argumentation framework. Such a portion is sufficient to compute the skeptical preferred acceptance of a goal argument w.r.t. the whole updated framework. We also discuss on how similar ideas extend to more general argumentation frameworks.
Artificial Intelligence
Cognition
Computational modeling
Computing Methodologies
Heuristic algorithms
Intelligent systems
Knowledge Representation Formalisms and Methods
Research and development
Semantics
Task analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/319724
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