Incremental computation of deterministic extensions for dynamic argumentation frameworks

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Abstract

We address the problem of efficiently recomputing the extensions of abstract argumentation frameworks (AFs) which are updated by adding/deleting arguments or attacks. In particular, after identifying some properties that hold for updates of AFs under several well-known semantics, we focus on the two most popular ‘deterministic’ semantics (namely, grounded and ideal) and present two algorithms for their incremental computation, well-suited to dynamic applications where updates to an initial AF are frequently performed to take into account new available knowledge. We experimentally validated the proposed approach.

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APA

Greco, S., & Parisi, F. (2016). Incremental computation of deterministic extensions for dynamic argumentation frameworks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10021 LNAI, pp. 288–304). Springer Verlag. https://doi.org/10.1007/978-3-319-48758-8_19

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