Argumentation is a human-like reasoning mechanism contributing to the formalization of commonsense reasoning. In the last decade, several argument-based formalisms have emerged, with application in many areas, such as legal reasoning, autonomous agents and multi-agent systems; many are based on Dung’s seminal work characterizing Abstract Argumentation Frameworks (AF). Recent research in the area has led to Temporal Argumentation Frameworks (TAF) that extend Dung’s by considering the temporal availability of arguments. In this work we introduce a novel framework, called Extended Temporal Argumentation Framework (E-TAF), extending TAF with the capability of modeling availability of attacks among arguments, which allows for instance to model reliability of arguments varying over time. We show how E-TAF can be enriched by considering Structured Abstract Argumentation, adding compositional elements to the abstract arguments involved based on a simplified version of the recently introduced Dynamic Argumentation Frameworks.

We deal with the problem of how to extend a preference relation over a set X of "objects" to the set of all subsets of X. This problem has been carried out in the tradition of the literature on extending an order on a set to its power set with the objective to analyze the axiomatic structure of families of rankings over subsets. In particular, most of these approaches make use of axioms aimed to prevent any kind of interaction among the objects in X . In this paper, we apply coalitional games to study the problem of extending preferences over a finite set X to its power set 2 X . A coalitional game can be seen as a numerical representation of a preference extension on 2 X . . We focus on a particular class of extensions on 2 X . such that the ranking induced by the Shapley value of each coalitional game representing an extension in this class, coincides with the original preference on X . Some properties of Shapley extensions are discussed, with the objective to justify and contextualize the application of Shapley extensions to the problem of ranking sets of possibly interacting objects.We deal with the problem of how to extend a preference relation over a set X of "objects" to the set of all subsets of X . This problem has been carried out in the tradition of the literature on extending an order on a set to its power set with the objective to analyze the axiomatic structure of families of rankings over subsets. In particular, most of these approaches make use of axioms aimed to prevent any kind of interaction among the objects in X . In this paper, we apply coalitional games to study the problem of extending preferences over a finite set X to its power set 2 X . . A coalitional game can be seen as a numerical representation of a preference extension on 2 X . . We focus on a particular class of extensions on 2 X. such that the ranking induced by the Shapley value of each coalitional game representing an extension in this class, coincides with the original preference on X . Some properties of Shapley extensions are discussed, with the objective to justify and contextualize the application of Shapley extensions to the problem of ranking sets of possibly interacting objects.

We present a system capable of automatically solving combinatorial logic puzzles given in (simplified) English. It uses an ontology to represent the puzzles in ASP which is applicable to a large set of logic puzzles. To translate the English descriptions of the puzzles into this ontology, we use a lambda-calculus based approach using Probabilistic Combinatorial Categorial Grammars (PCCG) where the meanings of words are associated with parameters to be able to distinguish between multiple meanings of the same word.

The paper introduces a worst-case optimal tableau algorithm for reasoning with Forest Logic Programs, a decidable fragment of Open Answer Set Programming. FoLPs are a useful device for tight integration of the Description Logic and the Logic Programming worlds: reasoning with the DL SHOQ can be simulated within the fragment. The algorithm reuses a knowledge compilation technique previously introduced, but improves on previous results by decreasing the worst-case running time with one exponential level. The decrease in complexity is due to the usage in conjunction of a new redundancy and of a new caching rule.

In ontology-based data access (OBDA), ontologies are used as an interface for querying instance data. Since in typical applications the size of the data is much larger than the size of the ontology and query, data complexity is the most important complexity measure. In this paper, we propose a new method for investigating data complexity in OBDA: instead of classifying whole logics according to their complexity, we aim at classifying each individual ontology within a given master language. Our results include a P/coNP-dichotomy theorem for ontologies of depth one in the description logic ALCFI, the equivalence of a P/coNP-dichotomy theorem for ALC/ALCI-ontologies of unrestricted depth to the famous dichotomy conjecture for CSPs by Feder and Vardi, and a non-P/coNP-dichotomy theorem for ALCF-ontologies.

While query answering in the presence of description logic (DL) ontologies is a well-studied problem, questions of static analysis such as query containment and query optimization have received less attention. In this paper, we study a rather general version of query containment that, unlike the classical version, cannot be reduced to query answering. First, we allow a restriction to be placed on the vocabulary used in the instance data, which can result in shorter equivalent queries; and second, we allow each query its own ontology rather than assuming a single ontology for both queries, which is crucial in applications to versioning and modularity. We also study global minimization of queries in the presence of DL ontologies, which is more subtle than for classical databases as minimal queries need not be isomorphic.

The EL family of description logics (DLs) has been designed to provide a restricted syntax for commonly used DL constructors with the goal to guarantee polynomial complexity of reasoning. Yet, polynomial complexity does not always mean that the underlying reasoning procedure is efficient inpractice. In this paper we consider a simple DL ELO from the EL family that admits nominals, and argue that existing polynomial reasoning procedures for ELO can be impractical for many realistic ontologies. To solve the problem, we describe an optimization strategy in which the inference rules required for reasoning with nominals are avoided as much as possible. The optimized procedure is evaluated within the reasoner ELK and demonstrated to perform well in practice.

Answer Set Programming (ASP) is a fully-declarative logic programming paradigm, which has been proposed in the area of knowledge representation and non-monotonic reasoning. Nowadays, the formal properties of ASP are well-understood, efficient ASP systems are available, and, recently, ASP has been employed in a few industrial applications. However, ASP technology is not mature for a successful exploitation in industry yet; mainly because ASP technologies are not integrated in the well-assessed development processes and platforms which are tailored for imperative/object-oriented programming languages. In this paper we present a new programming framework blending ASP with Java. The framework is based on JASP, an hybrid language that transparently supports a bilateral interaction between ASP and Java. JASP specifications are compliant with the JPA standard to perfectly fit extensively-adopted enterprise application technologies. The framework also encompasses an implementation of JASP as a plug-in for the Eclipse platform, called JDLV, which includes a compiler from JASP to Java. Moreover, we show a real-world application developed with JASP and JDLV, which highlights the effectiveness of our ASP–Java integration framework.

In software testing, the small-scope hypothesis states that a high proportion of errors can be found by testing a program for all test inputs within some small scope. In this paper, we evaluate the small-scope hypothesis for answer-set programming (ASP). To this end, we follow work in traditional testing and base our evaluation on mutation analysis. In fact, we show that a rather limited scope is sufficient for testing ASP encodings from a representative set of benchmark problems. Our experimental evaluation facilitates effective methods for testing in ASP. Also, it gives some justification to analyse programs at the propositional level after grounding them over a small domain.

In this paper we encode some of the reasoning methods used in frame based knowledge representation languages in answer set programming (ASP). In particular, we show how ``cloning'' and ``unification'' in frame based systems can be encoded in ASP. We then show how some of the types of queries with respect to a biological knowledge base can be encoded using our methodology. We also provide insight on how the reasoning can be done more efficiently when dealing with a huge knowledge base.