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Giacomin

AAAI Conferences

argumentation frameworks (AFs) are one of the central formalisms in AI; equipped with a wide range of semantics, they have proven useful in several application domains. We contribute to the systematic analysis of semantics for AFs by connecting two recent lines of research -- the work on input/output frameworks and the study of the expressiveness of semantics. We do so by considering the following question: given a function describing an input/output behaviour by mapping extensions (resp.


jArgSemSAT: An Efficient Off-the-Shelf Solver for Abstract Argumentation Frameworks

AAAI Conferences

In this report from the field we describe jArgSemSAT, a Java re-implementation of ArgSemSAT. We show that jArgSemSAT can be easily integrated in existing argumentation systems (1) as an off-the-shelf, standalone, library; (2) as a Tweety compatible library; and (3) as a fast and robust web service freely available on the Web. The performance section shows that — despite being written in Java — jArgSemSAT is very efficient w.r.t. preferred semantics, which has associated problems with high computational complexity.


On the Functional Completeness of Argumentation Semantics

AAAI Conferences

Abstract argumentation frameworks (AFs) are one of the central formalisms in AI; equipped with a wide range of semantics, they have proven useful in several application domains. We contribute to the systematic analysis of semantics for AFs by connecting two recent lines of research -- the work on input/output frameworks and the study of the expressiveness of semantics. We do so by considering the following question: given a function describing an input/output behaviour by mapping extensions (resp. labellings) to sets of extensions (resp. labellings), is there an AF with designated input and output arguments realizing this function under a given semantics? For the major semantics we give exact characterizations of the functions which are realizable in this manner.


Abstract Argumentation Frameworks — From Theoretical Insights to Practical Implications

AAAI Conferences

Abstract argumentation frameworks (AFs) are one of the central formalisms in AI; equipped with a wide range of semantics, they have proven useful in several application domains. In the thesis we want to complete and extend the recent study on expressiveness of argumentation semantics and use these and other theoretical results for implementations of reasoning tasks in AFs. Moreover, we plan to utilize results on realizability in dynamic scenarios of abstract argumentation, such as revision of argumentation frameworks. Hereby, the knowledge of which extensions can occur together is of central interest when trying to achieve a certain outcome. In other words, the ultimate goal of the thesis is to gain theoretical insights on argumentation semantics in order to employ them in practically efficient reasoning systems for both the evaluation and evolution of AFs.


Exploiting Parallelism for Hard Problems in Abstract Argumentation

AAAI Conferences

Abstract argumentation framework ( AF ) is a unifying framework able to encompass a variety of nonmonotonic reasoning approaches, logic programming and computational argumentation. Yet, efficient approaches for most of the decision and enumeration problems associated to AF s are missing, thus limiting the efficacy of argumentation-based approaches in real domains. In this paper, we present an algorithm for enumerating the preferred extensions of abstract argumentation frameworks which exploits parallel computation. To this purpose, the SCC-recursive semantics definition schema is adopted, where extensions are defined at the level of specific sub-frameworks. The algorithm shows significant performance improvements in large frameworks, in terms of number of solutions found and speedup.


Decision Support through Argumentation-Based Practical Reasoning

AAAI Conferences

To encompass them, several extensions of Dung's argumentation framework (AF) [Dung, This extended research abstract describes an 1995] have been proposed, but the most general, as shown in argumentation-based approach to modelling articulated [Baroni et al., 2011], is the Argumentation Framework with decision making contexts. The approach Recursive Attacks (AF RA) formalism [Baroni et al., 2009b; encompasses a variety of argument and attack 2011]. In[Baroni et al., 2009a; 2010b] we showed how to organise schemes aimed at representing basic knowledge arguments that are instances of argument schemes in and reasoning patterns for decision support.


Parametric Properties of Ideal Semantics

AAAI Conferences

The concept of "ideal semantics" has been promoted as an alternative basis for skeptical reasoning within abstract argumentation settings. Informally, ideal acceptance not only requires an argument to be skeptically accepted in the traditional sense but further insists that the argument is in an admissible set all of whose arguments are also skeptically accepted. The original proposal was couched in terms of the so-called preferred semantics for abstract argumentation. We argue, in this paper, that the notion of "deal acceptability'' is applicable to arbitrary semantics and justify this claim by showing that standard properties of classical ideal semantics, e.g. unique status, continue to hold in any "reasonable" extension-based semantics. We categorise the relationship between the divers concepts of "ideal extension wrt semantics s" that arise and we present a comprehensive analysis of algorithmic and complexity-theoretic issues.


Attack Semantics for Abstract Argumentation

AAAI Conferences

In this paper we conceptualize abstract argumentation in terms of successful and unsuccessful attacks, such that arguments are accepted when there are no successful attacks on them. We characterize the relation between attack semantics and Dung's approach, and we define an SCC recursive algorithm for attack semantics using attack labelings.