Giacomin, Massimiliano



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.


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.


Dealing with Generic Contrariness in Structured Argumentation

AAAI Conferences

The adoption of a generic contrariness notion in ASPIC+ substantially enhances its expressiveness with respect to other formalisms for structured argumentation. In particular, it opens the way to novel investigation directions, like the use of multivalued logics in the construction of arguments. This paper points out however that in the current version of ASPIC+ a serious technical difficulty related with generic contrariness is present. With the aim of preserving the same level of generality, the paper provides a solution based on a novel notion of closure of the contrariness relation at the level of sets of formulas and an abstract representation of conflicts between sets of arguments. The proposed solution is shown to satisfy the same rationality postulates as ASPIC+ and represents a starting point for further technical and conceptual developments in structured argumentation.


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.


Computing Preferred Extensions in Abstract Argumentation: a SAT-based Approach

arXiv.org Artificial Intelligence

This paper presents a novel SAT-based approach for the computation of extensions in abstract argumentation, with focus on preferred semantics, and an empirical evaluation of its performances. The approach is based on the idea of reducing the problem of computing complete extensions to a SAT problem and then using a depth-first search method to derive preferred extensions. The proposed approach has been tested using two distinct SAT solvers and compared with three state-of-the-art systems for preferred extension computation. It turns out that the proposed approach delivers significantly better performances in the large majority of the considered cases.


An Argumentation-Based Approach to Modeling Decision Support Contexts with What-If Capabilities

AAAI Conferences

This paper describes a preliminary proposal of an argumentation-based approach to modeling articulated decision support contexts. The proposed approach encompasses a variety of argument and attack schemes aimed at representing basic knowledge and reasoning patterns for decision support. Some of the defined attack schemes involve attacks directed towards other attacks, which are not allowed in traditional argumentation frameworks but turn out to be useful as a knowledge and reasoning modeling tool: in particular, we demonstrate their use to support what-if reasoning capabilities, which are of primary importance in decision support. Formal backing to this approach is provided by the AFRA formalism, a recently proposed extension of Dung’s argumentation framework. A literature example concerning a decision problem about medical treatments is adopted to illustrate the approach.


Computational Properties of Resolution-based Grounded Semantics

AAAI Conferences

In the context of Dung's theory of abstract argumentation frameworks, the recently introduced resolution-based grounded semantics features the unique property of fully complying with a set of general requirements, only partially satisfied by previous literature proposals. This paper contributes to the investigation of resolution-based grounded semantics by analyzing its computational properties with reference to a standard set of decision problems for abstract argumentation semantics: (a) checking the property of being an extension for a set of arguments; (b) checking agreement with traditional grounded semantics; (c) checking the existence of a non-empty extension; (d) checking credulous acceptance of an argument; (e) checking skeptical acceptance of an argument. It is shown that problems (a)-(c) admit polynomial time decision processes, while (d) is NP-complete and (e) coNP-complete.