Dynamics in Abstract Argumentation Frameworks with Recursive Attack and Support Relations

SEBASTIAN GOTTIFREDI; GUILLERMO R. SIMARI; ANDREA COHEN; FRANCESCO PARISI; GIANVINCENZO ALFANO; SERGIO GRECO

Santiago de Compostela

Conferencia; European Conference on Artificial Intelligence; 2020

European Association for Artificial Intelligence

Argumentation is an important topic in the field of AI. There is a substantial amount of work about different aspects of Dung?s abstract Argumentation Framework (AF). Two relevant aspects considered separately so far are extending the framework to account for recursive attacks and supports, and considering dynamics, i.e., AFs evolving over time. In this paper, we jointly deal with these two aspects. We focus on Attack-Support Argumentation Frameworks (ASAFs) which allow for attack and support relations not only between arguments but also targeting attacks and supports at any level, and propose an approach for the incremental computation of extensions (sets of accepted arguments, attacks and supports) of up dated ASAFs. Our approach assumes that an initial ASAF extension is given and uses it for first checking whether updates are irrelevant; for relevant updates, an extension of an updated ASAF is computed by translating the problem to the AF domain and leveraging on AF solvers. We experimentally show our incremental approach outperforms the direct computation of extensions for updated ASAFs.