High-Level Knowledge Representation and Reasoning in a Cognitive IoT/WoT Context

International audienceThis chapter presents an overview of the Generalized World Entities (GWEs) paradigm, used to add a semantic/conceptual dimension to the ordinary IoT/WoT procedures. Its purpose is to expand the range of entities to be considered when describing a sensor-monitored environment by allowing, in particular, to seamlessly model in a unified way (i.e., within the same representation framework) physical entities like objects, humans, robots, etc. and higher levels of abstraction structures corresponding to general situations/actions/events/behaviours. The unifying factor is provided by the conceptual representation of the world used for modelling the GWEs of both types. This is ontology-based and general enough to take into account both the “static” (background information about, e.g., common notions like robot, person or physical object) and the “dynamic” (foreground information concerning, e.g., a robot or a person moving in real time towards a given object) characteristics of the different entities to deal with. After having presented a short state of the art in the cognitive/semantic IoT/WoT domain, we will specify the notion of GWE by describing its implementation under NKRL (Narrative Knowledge Representation Language) format. NKRL is a high-level modelling language, whose main characteristic concerns the use of two ontologies, an ontology of standard concepts and an ontology of events, this last dealing with the representation of the dynamic and spatio-temporal characterized information denoting behaviours, complex events, situations, circumstances etc. We will show, using several examples, that this dichotomy allows us to effectively model, in a seamlessly way, all the different entities managed by the usual IoT/WoT procedures

Premier aperçu sur la construction de systèmes experts : «les machines de l'intelligence artificielle»

Zarri Gian Piero. Premier aperçu sur la construction de systèmes experts : «les machines de l'intelligence artificielle». In: Le médiéviste et l'ordinateur, N°16, automne 1986. L’édition électronique. pp. 35-42

Use of a Knowledge Patterns-Based Tool for Dealing With the “Narrative Meaning” of Complex Iconographic Cultural Heritage Items

International audienceThis paper suggests to use a powerful tool like NKRL, the “Narrative Knowledge Representation Language”, to deal with the representation and man- agement in digital form of those important Cultural Heritage entities correspond- ing to the “Iconographic Narratives”. These denote the “stories” conveyed by paintings, drawings, frescoes, mosaics, sculptures, murals and similar but also by pictures, posters, comics, cartoons, movies etc. An example of use of NKRL to deal with the complex narrative situation represented by the central scene of Di- ego Velazquez’s “The Surrender of Breda” is included in the paper

Fifth International Symposium on "Computers in Literary and Linguistic Research"

Zarri Gian Piero. Fifth International Symposium on "Computers in Literary and Linguistic Research". In: Le médiéviste et l'ordinateur, N°1, printemps 1979. pp. 15-16

Présentation. Où en est-on aujourd'hui ? L'IA, Mythe et réalité

Zarri Gian Piero. Présentation. Où en est-on aujourd'hui ? L'IA, Mythe et réalité. In: Le médiéviste et l'ordinateur, Numéro spécial,1990. Actes de la Table ronde (Paris, CNRS, 17 novembre 1989) pp. 171-172

Construction de grandes bases de connaissances selon l’approche “intelligence artificielle intégrale”

Zarri Gian Piero. Construction de grandes bases de connaissances selon l’approche “intelligence artificielle intégrale”. In: Le médiéviste et l'ordinateur, N°19, printemps 1988. Le renouveau de la recherche documentaire. pp. 22-26

Une méthode d’encodage automatique pour l’accès à RÉSÉDA

Zarri Gian Piero. Une méthode d’encodage automatique pour l’accès à RÉSÉDA . In: Le médiéviste et l'ordinateur, N°15, printemps 1986. Quand l'ordinateur devient intelligent. pp. 2-5

Advanced computational reasoning based on the NKRL conceptual model

International audienceAfter having recalled some well-known shortcomings linked with the Semantic Web approach to the creation of (application oriented) systems of “rules” – e.g., limited expressiveness, adoption of an Open World Assumption (OWA) paradigm, absence of variables in the original definition of OWL – this paper examines the technical solutions successfully used for implementing advanced reasoning systems according to the NKRL’s methodology. NKRL (Narrative Knowledge Representation Language) is a conceptual meta-model and a Computer Science environment expressly created to deal, in an ‘intelligent’ and complete way, with complex and content-rich non-fictional ‘narrative’ data sources. These last include corporate memory documents, news stories, normative and legal texts, medical records, surveillance videos, actuality photos for newspapers and magazines, etc. In this context, we will expound first the need for distinguishing between “plain/static” and “structured/dynamic” knowledge and for introducing appropriate (and different) knowledge representation structures for these two types of knowledge. In a structured/dynamic context, we will then show how the introduction of “functional roles” – associated with the possibility of making use of n-ary structures – allows us to build up highly ‘expressive’ rules whose “atoms” can directly represent complex situations, actions, etc. without being restricted to the use of binary clauses. In an NKRL context, “functional roles” are primitive symbols interpreted as “relations” – like “subject”, “object”, “source”, “beneficiary”, etc. – that link a semantic predicate with its arguments within an n-ary conceptual formula. Functional roles contrast then with the “semantic roles” that are equated to ordinary concepts like “student”, to be inserted into the “non-sortal” (no direct instances) branch of a traditional ontology