ATOME : a blackboard architecture with temporal and hypothetical reasoning

To cope with high level AI-based applications as signal understanding, process control or decision making, an AI system must take into account various knowledge sources and reasoning schemes. In this paper, we propose a blackboard-based architecture which achieves opportunism and efficiency while controlling multiple knowledge sources. In addition it integrates temporal and hypothetical reasoning to deal with applications evolving in time, and manipulating noisy or errorfull information

Le raisonnement en intelligence artificielle

International audienceFruit d'un travail d'enseignement et de recherche mené au Centre de Recherche en Informatique de Nancy (CRIN-CNRS/INRIA-Lorraine), cet ouvrage constitue l'une des premières présentations unifiées des divers modèles, techniques et architectures de raisonnement qui interviennent dans les systèmes à bases de connaissances.Après une introduction au domaine des systèmes à bases de connaissances dans le cadre général de l'intelligence Artificielle, ou I.A., les auteurs abordent la logique mathématique et ses liens avec le raisonnement, le raisonnement approximatif et incertain et les ensembles flous. Ils se consacrent ensuite au problème du temps dans les raisonnements et aux raisonnements hypothétique, qualitatif, par classification et analogique. Le dernier chapitre porte sur le raisonnement multi-agents dans le cadre de l'IA distribuée et prête une attention toute particulière au modèle de tableau noir.Constituant une référence précieuse pour comprendre et mettre en oeuvre les raisonnements nécessaires aux systèmes d'I.A. d'aujourd'hui et de demain, ce livre s'adresse aussi bien à l'ingénieur et au chef de projets amenés à développer de tels systèmes qu'au chercheur en I.A., à l'enseignant et à l'étudiant, de maîtrise ou de troisième cycle

Le raisonnement en intelligence artificielle

International audienceFruit d'un travail d'enseignement et de recherche mené au Centre de Recherche en Informatique de Nancy (CRIN-CNRS/INRIA-Lorraine), cet ouvrage constitue l'une des premières présentations unifiées des divers modèles, techniques et architectures de raisonnement qui interviennent dans les systèmes à bases de connaissances.Après une introduction au domaine des systèmes à bases de connaissances dans le cadre général de l'intelligence Artificielle, ou I.A., les auteurs abordent la logique mathématique et ses liens avec le raisonnement, le raisonnement approximatif et incertain et les ensembles flous. Ils se consacrent ensuite au problème du temps dans les raisonnements et aux raisonnements hypothétique, qualitatif, par classification et analogique. Le dernier chapitre porte sur le raisonnement multi-agents dans le cadre de l'IA distribuée et prête une attention toute particulière au modèle de tableau noir.Constituant une référence précieuse pour comprendre et mettre en oeuvre les raisonnements nécessaires aux systèmes d'I.A. d'aujourd'hui et de demain, ce livre s'adresse aussi bien à l'ingénieur et au chef de projets amenés à développer de tels systèmes qu'au chercheur en I.A., à l'enseignant et à l'étudiant, de maîtrise ou de troisième cycle

Calibration of Elasto-Magnetic Sensors on In-Service Cable-Stayed Bridges for Stress Monitoring

The recent developments in measurement technology have led to the installation of efficient monitoring systems on many bridges and other structures all over the world. Nowadays, more and more structures have been built and instrumented with sensors. However, calibration and installation of sensors remain challenging tasks. In this paper, we use a case study, Adige Bridge, in order to present a low-cost method for the calibration and installation of elasto-magnetic sensors on cable-stayed bridges. Elasto-magnetic sensors enable monitoring of cable stress. The sensor installation took place two years after the bridge construction. The calibration was conducted in two phases: one in the laboratory and the other one on site. In the laboratory, a sensor was built around a segment of cable that was identical to those of the cable-stayed bridge. Then, the sample was subjected to a defined tension force. The sensor response was compared with the applied load. Experimental results showed that the relationship between load and magnetic permeability does not depend on the sensor fabrication process except for an offset. The determination of this offset required in situ calibration after installation. In order to perform the in situ calibration without removing the cables from the bridge, vibration tests were carried out for the estimation of the cables’ tensions. At the end of the paper, we show and discuss one year of data from the elasto-magnetic sensors. Calibration results demonstrate the simplicity of the installation of these sensors on existing bridges and new structures

The activation energy

It is reported in this paper on the thermally assisted flux flow in epitaxial YBa2Cu3O7-δ deposited by Laser ablation method on the SrTiO3 substrate. The resistivity measurements ρ (T, B) of the sample under various values of the magnetic field up to 14T in directions B∥ab-plane and B∥c-axis with a dc weak transport current density were investigated in order to determine the activation energy and then understand the vortex dynamic phenomena and therefore deduce the vortex phase diagram of this material. The apparent activation energy U0 (B) calculated using an Arrhenius relation. The measured results of the resistivity were then adjusted to the modified thermally assisted flux flow model in order to account for the temperature-field dependence of the activation energy U (T, B). The obtained values from the thermally assisted activation energy, exhibit a behavior similar to the one showed with the Arrhenius model, albeit larger than the apparent activation energy with ∼1.5 order on magnitude for both cases of the magnetic field directions. The vortex glass model was also used to obtain the vortex-glass transition temperature from the linear fitting of [d ln ρ/dT ] −1 plots. In the course of this work thanks to the resistivity measurements the upper critical magnetic field Hc2 (T), the irreversibility line Hirr (T) and the crossover field HCrossOver (T) were located. These three parameters allowed us to establish a phase diagram of the studied material where limits of each vortex phase are sketched in order to optimize its applicability as a practical high temperature superconductor used for diverse purposes

A fuzzy expert system for automatic seismic signal classification

Automatic classification of seismic events is of great importance due to the large amount of data received continuously. Seismic analysts classify events by visual inspection and calculation of event signal characteristics. This process is subjective and demands hard work as well as a significant amount of time and considerable experience. A reliable automatic classification task considerably reduces the effort required and makes classification faster and more objective. The aim of this study is to develop a fuzzy rule based expert classification system that is able to imitate human reasoning and incorporate the analyst's knowledge of seismic event classification. The fundamental idea behind using this approach was motivated by the way in which human analysts classify seismic events based on a set of experiential rules. Additionally, this approach was chosen due to its interpretability and adjustability, as well as its ability to manage the complexity of real data. Relevant discriminant features are extracted from event signal. Using these features, the classification system was built based on the vote by multiple rule fuzzy reasoning method with three types of rules. Comparison of this method with the single winner classical fuzzy reasoning model was carried out. Classification results on real seismic data showed the robustness of the classifier and its capability to operate in on-line classification

ATOME : a blackboard architecture with temporal and hypothetical reasoning

SIGLECNRS 14802 E / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Raisonnement multi-agents

SIGLEAvailable at INIST (FR), Document Supply Service, under shelf-number : RP 11127 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Cooperating expert problem solving in blackboard systems ATOME case study

Proceedings Workshop on modelling an autonomous agent in a multi-agents world, Cambridge (England), August 1989SIGLEAvailable at INIST (FR), Document Supply Service, under shelf-number : RP 10735 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc