Sergio Alejandro Gómez

REASONING WITH INCONSISTENT ONTOLOGIES THROUGH ARGUMENTATION

Standard approaches to reasoning with description logics (DL) ontologies require them to be consistent. However, as ontologies are complex entities and sometimes built upon other imported ontologies, inconsistencies can arise. In this article, we present δ-ontologies, a framework for reasoning with inconsistent DL ontologies. Our proposal involves expressing DL ontologies as defeasible logic programs (DeLP). Given a query posed w.r.t. an inconsistent ontology, a dialectical analysis will be performed on a DeLP program obtained from such an ontology, where all arguments in favor and against the final answer of the query will be taken into account. We also present an application to ontology integration based on the global-as-view approach.

ONTOarg: A decision support framework for ontology integration based on argumentation

Description Logic Programming (DLP) is a well-known approach to reason with Description Logic (DL) ontologies, translating them into the language of logic programming (LP). Even though DLP offers several advantages in terms of efficiency and reuse of existing logic programming tools (such as Prolog environments), a major hindrance of this approach is its limitation for reasoning in the presence of inconsistent ontologies. Recent research has led to the use of defeasible argumentation to model different DL reasoning capabilities when handling inconsistent ontologies, resulting in so-called @d-ontologies. In this article we present ONTOarg, a decision support framework for performing local-as-view integration of possibly inconsistent and incomplete ontologies in terms of Defeasible Logic Programming (DeLP). We show how to reason on Description Logics (DL) ontologies in an ontology integration system by performing a dialectical analysis in order to determine the membership of individuals to concepts. We present formal definitions of a framework for ontology integration of DL ontologies based on DeLP along with a case study and review some of the properties of the approach.

DEFEASIBLE REASONING IN WEB-BASED FORMS THROUGH ARGUMENTATION

The notion of forms as a way of organizing and presenting data has been used since the beginning of the World Wide Web. Web-based forms have evolved together with the development of new markup languages, in which it is possible to provide validation scripts as part of the form code to test whether the intended meaning of the form is correct. However, for the form designer, part of this intended meaning frequently involves other features which are not constraints by themselves, but rather attributes emerging from the form, which provide plausible conclusions in the context of incomplete and potentially inconsistent information. As the value of such attributes may change in presence of new knowledge, we call them defeasible attributes. In this paper, we propose extending traditional web-based forms to incorporate defeasible attributes as part of the knowledge that can be encoded by the form designer. The proposed extension allows the specification of scripts for reasoning about form fields using a defeasible knowledge base, expressed in terms of a Defeasible Logic Program.

Assuring safety in air traffic control systems with argumentation and model checking

We present a framework to model a recommender system for an air traffic control.We combine argumentation and model checking for doing model update in Hybrid Logics.We apply our approach to model repair in an unmanned aerial vehicle.We extend Defeasible Logic Programming to perform continuous reasoning. Although the continuous safety technology advances in fields like air traffic control (ATC) systems or medical devices, the crux of safety assurance still comes down to human decision makers, which, within the context of having to define priorities while simultaneously considering different contextual criteria, present a constant high risk of erroneous decisions. We illustrate in this article a recommender framework for assisting flight controllers, which combines argumentation theory and model checking in the evaluation of trade-offs and compromises to be made in the presence of incomplete and potentially inconsistent information. We view a Hybrid Kripke model as a description of an ATC domain and we apply a rational decision strategy based on Hybrid Logics and Defeasible Reasoning to assist the process of model update when the system has to accommodate new properties or norm constraints. When the model fails to verify a property, a defeasible logic program is used to analyze the current state and perform updating operations on the model. The introduced decision making framework is tested on a recommender system in ATC and model update is demonstrated with respect to the verification and adaption of unmanned aerial vehicles routes in the air traffic space. The results show an important potential for the presented framework to be integrated directly into existing decision-making routines for achieving higher accuracy in recommender system methods.

Reasoning with Inconsistent Possibilistic Ontologies by Applying Argument Accrual

We present an approach for performing instance checking in possibilistic description logic programming ontologies by accruing arguments that support the membership of individuals to concepts. Ontologies are interpreted as possibilistic logic programs where accruals of arguments as regarded as vertexes in an abstract argumentation framework. A suitable attack relation between accruals is defined. We present a reasoning framework with a case study and a Java-based implementation for enacting the proposed approach that is capable of reasoning under Dung’s grounded semantics.

An Argumentative Approach to Assessing Safety in Medical Device Software Using Defeasible Logic Programming

Modern health-care technology depends to a large extent on software deployed in medical devices, which brings several well-known benefits but also poses new hazards to patient safety. As a consequence, assessing safety and reliability in software in medical devices turns out to be a critical issue. In this paper we outline a method for safety assessment of medical devices based on Defeasible Logic Programming (DeLP), which provides an argumentative framework for reasoning with uncertain and incomplete knowledge.We contend that argumentation theory as defined in DeLP can be used to integrate and contrast different evidences for assessing the approval and commercialization of medical devices, aiming at increasing transparency to all the stakeholders involved in their certification. The outlined framework is validated by modeling the infamous Therac-25 accident.