Ontology: Towards a new synthesis

This introduction to the second international conference on Formal Ontology and Information Systems presents a brief history of ontology as a discipline spanning the boundaries of philosophy and information science. We sketch some of the reasons for the growth of ontology in the information science field, and offer a preliminary stocktaking of how the term ‘ontology’ is currently used. We conclude by suggesting some grounds for optimism as concerns the future collaboration between philosophical ontologists and information scientists

LoLa: a modular ontology of logics, languages and translations

The Distributed Ontology Language (DOL), currently being standardised within the OntoIOp (Ontology Integration and Interoperability) activity of ISO/TC 37/SC 3, aims at providing a unified framework for (i) ontologies formalised in heterogeneous logics, (ii) modular ontologies, (iii) links between ontologies, and (iv) annotation of ontologies.\ud \ud This paper focuses on the LoLa ontology, which formally describes DOL's vocabulary for logics, ontology languages (and their serialisations), as well as logic translations. Interestingly, to adequately formalise the logical relationships between these notions, LoLa itself needs to be axiomatised heterogeneously---a task for which we choose DOL. Namely, we use the logic RDF for ABox assertions, OWL for basic axiomatisations of various modules concerning logics, languages, and translations, FOL for capturing certain closure rules that are not expressible in OWL (For the sake of tool availability it is still helpful not to map everything to FOL.), and circumscription for minimising the extension of concepts describing default translations

The Pyglaf Argumentation Reasoner

The pyglaf reasoner takes advantage of circumscription to solve computational problems of abstract argumentation frameworks. In fact, many of these problems are reduced to circumscription by means of linear encodings, and a few others are solved by means of a sequence of calls to an oracle for circumscription. Within pyglaf, Python is used to build the encodings and to control the execution of the external circumscription solver, which extends the SAT solver glucose and implements an algorithm based on unsatisfiable core analysis

Local logics, non-monotonicity and defeasible argumentation

In this paper we present an embedding of abstract argumentation systems into the framework of Barwise and Seligman’s logic of information flow.We show that, taking P.M. Dung’s characterization of argument systems, a local logic over states of a deliberation may be constructed. In this structure, the key feature of non-monotonicity of commonsense reasoning obtains as the transition from one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions of Barwise and Seligman’s logic of information flow.We show that, taking P.M. Dung’s characterization of argument systems, a local logic over states of a deliberation may be constructed. In this structure, the key feature of non-monotonicity of commonsense reasoning obtains as the transition from one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions of Barwise and Seligman’s logic of information flow.We show that, taking P.M. Dung’s characterization of argument systems, a local logic over states of a deliberation may be constructed. In this structure, the key feature of non-monotonicity of commonsense reasoning obtains as the transition from one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions of Barwise and Seligman’s logic of information flow.We show that, taking P.M. Dung’s characterization of argument systems, a local logic over states of a deliberation may be constructed. In this structure, the key feature of non-monotonicity of commonsense reasoning obtains as the transition from one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions of Barwise and Seligman’s logic of information flow.We show that, taking P.M. Dung’s characterization of argument systems, a local logic over states of a deliberation may be constructed. In this structure, the key feature of non-monotonicity of commonsense reasoning obtains as the transition from one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions one local logic to another, due to a change in certain background conditions. Each of Dung’s extensions of argument systems leads to a corresponding ordering of background conditions. The relations among extensions becomes a relation among partial orderings of background conditions. This introduces a conceptual innovation in Barwise and Seligman’s representation of commonsense reasoning.Fil: Bodanza, Gustavo Adrian. Universidad Nacional del Sur. Departamento de Humanidades; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; ArgentinaFil: Tohmé, Fernando Abel. Universidad Nacional del Sur. Departamento de Economía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentin

Logical Omnipotence and Two notions of Implicit Belief

The most widespread models of rational reasoners (the model based on modal epistemic logic and the model based on probability theory) exhibit the problem of logical omniscience. The most common strategy for avoiding this problem is to interpret the models as describing the explicit beliefs of an ideal reasoner, but only the implicit beliefs of a real reasoner. I argue that this strategy faces serious normative issues. In this paper, I present the more fundamental problem of logical omnipotence, which highlights the normative content of the problem of logical omniscience. I introduce two developments of the notion of implicit belief (accessible and stable belief ) and use them in two versions of the most common strategy applied to the problem of logical omnipotence

How to Complete an Interactive Configuration Process?

When configuring customizable software, it is useful to provide interactive tool-support that ensures that the configuration does not breach given constraints. But, when is a configuration complete and how can the tool help the user to complete it? We formalize this problem and relate it to concepts from non-monotonic reasoning well researched in Artificial Intelligence. The results are interesting for both practitioners and theoreticians. Practitioners will find a technique facilitating an interactive configuration process and experiments supporting feasibility of the approach. Theoreticians will find links between well-known formal concepts and a concrete practical application.Comment: to appear in SOFSEM 201