XAI: Using Smart Photobooth for Explaining History of Art

The rise of Artificial Intelligence has led to advancements in daily life, including applications in industries, telemedicine, farming, and smart cities. It is necessary to have human-AI synergies to guarantee user engagement and provide interactive expert knowledge, despite AI’s success in "less technical" fields. In this article, the possible synergies between humans and AI to explain the development of art history and artistic style transfer are discussed. This study is part of the "Smart Photobooth" project that is able to automatically transform a user’s picture into a well-known artistic style as an interactive approach to introduce the fundamentals of the history of art to the common people and provide them with a concise explanation of the various art painting styles. This study investigates human-AI synergies by combining the explanation produced by an explainable AI mechanism with a human expert’s insights to provide reasons for school students and a larger audience

Modèle dynamique multiniveau et holonique pour la simulation d'un système complexe à grande échelle avec environnement spatial : Application à la simulation du trafic routier

De nos jours, avec l’émergence d’objets et de voitures connectés, les systèmes de trafic routier deviennent de plus en plus complexes et présentent des comportements hiérarchiques à plusieurs niveaux de détail. L'approche de modélisation multiniveaux est une approche appropriée pour représenter le trafic sous plusieurs perspectives. Les modèles multiniveaux constituent également une approche appropriée pour modéliser des systèmes complexes à grande échelle comme le trafic routier. Cependant, la plupart des modèles multiniveaux de trafic proposés dans la littérature sont statiques car ils utilisent un ensemble de niveaux de détail prédéfinis et ces représentations ne peuvent pas commuter pendant la simulation. De plus ces modèles multiniveaux considèrent généralement seulement deux niveaux de détail. Très peu de travaux se sont intéressés à la modélisation dynamique multiniveau de trafic.Cette thèse propose un modèle holonique multiniveau et dynamique du trafic à grande échelle.La commutation dynamique des niveaux de détail lors de l’exécution de la simulation permet d’adapter le modèle aux contraintes liées à la qualité des résultats ou aux ressources de calcul disponibles.La proposition étend l'algorithme DBSCAN dans le contexte des systèmes multi-agents holoniques. De plus, une méthodologie permettant la commutation dynamique entre les différents niveaux de détail est proposée. Des indicateurs multiniveaux basés sur l'écart type sont aussi proposés afin d'évaluer la cohérence des résultats de la simulation.Nowadays, with the emergence of connected objects and cars, road traffic systems become more and more complex and exhibit hierarchical behaviours at several levels of detail. The multilevel modeling approach is an appropriate approach to represent traffic from several perspectives. Multilevel models are also an appropriate approach to model large-scale complex systems such as road traffic. However, most of the multilevel models of traffic proposed in the literature are static because they use a set of predefined levels of detail and these representations cannot change during simulation. Moreover, these multilevel models generally consider only two levels of detail. Few works have been interested on the dynamic multilevel traffic modeling.This thesis proposes a holonic multilevel and dynamic traffic model for large scale traffic systems. The dynamic switching of the levels of detail during the execution of the simulation allows to adapt the model to the constraints related to the quality of the results or to the available computing resources.The proposal extends the DBSCAN algorithm in the context of holonic multi-agent systems. In addition, a methodology allowing a dynamic transition between the different levels of detail is proposed. Multilevel indicators based on standard deviation are also proposed in order to assess the consistency of the simulation results

Modèle dynamique multiniveau et holonique pour la simulation d'un système complexe à grande échelle avec environnement spatial : Application à la simulation du trafic routier

Nowadays, with the emergence of connected objects and cars, road traffic systems become more and more complex and exhibit hierarchical behaviours at several levels of detail. The multilevel modeling approach is an appropriate approach to represent traffic from several perspectives. Multilevel models are also an appropriate approach to model large-scale complex systems such as road traffic. However, most of the multilevel models of traffic proposed in the literature are static because they use a set of predefined levels of detail and these representations cannot change during simulation. Moreover, these multilevel models generally consider only two levels of detail. Few works have been interested on the dynamic multilevel traffic modeling.This thesis proposes a holonic multilevel and dynamic traffic model for large scale traffic systems. The dynamic switching of the levels of detail during the execution of the simulation allows to adapt the model to the constraints related to the quality of the results or to the available computing resources.The proposal extends the DBSCAN algorithm in the context of holonic multi-agent systems. In addition, a methodology allowing a dynamic transition between the different levels of detail is proposed. Multilevel indicators based on standard deviation are also proposed in order to assess the consistency of the simulation results.De nos jours, avec l’émergence d’objets et de voitures connectés, les systèmes de trafic routier deviennent de plus en plus complexes et présentent des comportements hiérarchiques à plusieurs niveaux de détail. L'approche de modélisation multiniveaux est une approche appropriée pour représenter le trafic sous plusieurs perspectives. Les modèles multiniveaux constituent également une approche appropriée pour modéliser des systèmes complexes à grande échelle comme le trafic routier. Cependant, la plupart des modèles multiniveaux de trafic proposés dans la littérature sont statiques car ils utilisent un ensemble de niveaux de détail prédéfinis et ces représentations ne peuvent pas commuter pendant la simulation. De plus ces modèles multiniveaux considèrent généralement seulement deux niveaux de détail. Très peu de travaux se sont intéressés à la modélisation dynamique multiniveau de trafic.Cette thèse propose un modèle holonique multiniveau et dynamique du trafic à grande échelle.La commutation dynamique des niveaux de détail lors de l’exécution de la simulation permet d’adapter le modèle aux contraintes liées à la qualité des résultats ou aux ressources de calcul disponibles.La proposition étend l'algorithme DBSCAN dans le contexte des systèmes multi-agents holoniques. De plus, une méthodologie permettant la commutation dynamique entre les différents niveaux de détail est proposée. Des indicateurs multiniveaux basés sur l'écart type sont aussi proposés afin d'évaluer la cohérence des résultats de la simulation

A Cyber-Physical System for Semi-autonomous Oil & Gas Drilling Operations

International audienceIn Oil&Gas drilling operations and after reaching deep drilled depths, high temperature increases significantly enough to damage the down-hole drilling tools, and the existing mitigation process is insufficient. In this paper, we propose a Cyber-Physical System (CPS) where agents are used to represent the collaborating entities in Oil\&Gas fields both up-hole and down-hole. With the proposed CPS, down-hole tools respond to high temperature autonomously with a decentralized collective voting based on the tools' internal decision model while waiting for the cooling performed up-hole by the field engineer. This decision model, driven by the tools' specifications, aims to withstand high temperature. The proposed CPS is implemented using a multiagent simulation environment, and the results show that it mitigates high temperature properly with both the voting and the cooling mechanisms

Between the Megalopolis and the Deep Blue Sky: Challenges of Transport with UAVs in Future Smart Cities

International audienceWith the rapid increase of the world's urban population, the infrastructure of the constantly expanding metropolitan areas is undergoing an immense pressure. To meet the growing demands of sustainable urban environments and improve the quality of life for citizens, municipalities will increasingly rely on novel transport solutions. In particular, Unmanned Aerial Vehicles (UAVs) are expected to have a crucial role in the future smart cities thanks to their interesting features such as autonomy, flexibility, mobility, adaptive altitude, and small dimensions. However, densely populated megalopolises of the future are administrated by several municipals, governmental and civil society actors, where vivid economic activities involving a multitude of individual stakeholders take place. In such megalopolises, the use of agents for UAVs is gaining more interest especially in complex application scenarios where coordination and cooperation are necessary. This paper sketches a visionary view of the UAVs' role in the transport domain of future smart cities. Additionally, four challenging research directions are highlighted including problems related to autonomy, explainability, security and validation & verification of the UAVs behavior