4,837 research outputs found
Some Supplementaries to The Counting Semantics for Abstract Argumentation
Dung's abstract argumentation framework consists of a set of interacting
arguments and a series of semantics for evaluating them. Those semantics
partition the powerset of the set of arguments into two classes: extensions and
non-extensions. In order to reason with a specific semantics, one needs to take
a credulous or skeptical approach, i.e. an argument is eventually accepted, if
it is accepted in one or all extensions, respectively. In our previous work
\cite{ref-pu2015counting}, we have proposed a novel semantics, called
\emph{counting semantics}, which allows for a more fine-grained assessment to
arguments by counting the number of their respective attackers and defenders
based on argument graph and argument game. In this paper, we continue our
previous work by presenting some supplementaries about how to choose the
damaging factor for the counting semantics, and what relationships with some
existing approaches, such as Dung's classical semantics, generic gradual
valuations. Lastly, an axiomatic perspective on the ranking semantics induced
by our counting semantics are presented.Comment: 8 pages, 3 figures, ICTAI 201
Computing Argumentation with Matrices
Abstract argumentation frameworks with finitely many arguments can be presented in matrix form. For this reason, the strengths and weaknesses of matrix operations are migrated from a mathematical representation to a computer science interpretation. We present matrix operation algorithms that can answer whether a given set of arguments is part of an argumentation extension
Dynamics in Abstract Argumentation Frameworks with Recursive Attack and Support Relations
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 updated 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.Fil: Alfano, Gianvincenzo. Universita Della Calabria.; ItaliaFil: Cohen, Andrea. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - BahÃa Blanca. Instituto de Ciencias e IngenierÃa de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e IngenierÃa de la Computación. Instituto de Ciencias e IngenierÃa de la Computación; ArgentinaFil: Gottifredi, Sebastian. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - BahÃa Blanca. Instituto de Ciencias e IngenierÃa de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e IngenierÃa de la Computación. Instituto de Ciencias e IngenierÃa de la Computación; ArgentinaFil: Greco, Sergio. Universita Della Calabria.; ItaliaFil: Parisi, Francesco. Universita Della Calabria.; ItaliaFil: Simari, Guillermo R.. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - BahÃa Blanca. Instituto de Ciencias e IngenierÃa de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e IngenierÃa de la Computación. Instituto de Ciencias e IngenierÃa de la Computación; Argentina24th European Conference on Artificial IntelligenceSantiago de CompostelaEspañaEuropean Association for Artificial IntelligenceUniversidad de Santiago de Compostel
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