Principles and Experimentations of Self-organizing Embedded Agents Allowing Learning from Demonstration in Ambient Robotic. - Nicolas Verstaevel; Christine Régis; Marie-Pierre Gleizes; Fabrice Robert (ANT/SEIT, 2015)

The Self-Adaptive Context Learning Pattern: Overview and Proposal. - Jérémy Boes; Julien Nigon; Nicolas Verstaevel; Marie-Pierre Gleizes; Frédéric Migeon (CONTEXT, 2015)

Extreme Sensitive Robotic - A Context-Aware Ubiquitous Learning. - Nicolas Verstaevel; Christine Régis; Valérian Guivarch; Marie-Pierre Gleizes; Fabrice Robert (ICAART (1), 2015)

Auto-organisation d'agents embarqués pour l'apprentissage par démonstration : principes et expérimentations (présentation courte). - Nicolas Verstaevel; Christine Régis; Marie-Pierre Gleizes; Fabrice Robert (JFSMA, 2015)

Principles and experimentations of self-organizing embedded agents allowing learning from demonstration in ambient robotics. - Nicolas Verstaevel; Christine Régis; Marie-Pierre Gleizes; Fabrice Robert (Future Gener. Comput. Syst., 2016)

Smart Is a Matter of Context. - Julien Nigon; Nicolas Verstaevel; Jérémy Boes; Frédéric Migeon; Marie-Pierre Gleizes (CONTEXT, 2017)

Lifelong Machine Learning with Adaptive Multi-Agent Systems. - Nicolas Verstaevel; Jérémy Boes; Julien Nigon; Dorian d'Amico; Marie-Pierre Gleizes (ICAART (2), 2017)

Impact of eco-feedback on the behavior of campus users. - Paul Piche; Elhadi Belghache; Nicolas Verstaevel; Bérangère Lartigue (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI, 2017)

From smart campus to smart cities issues of the smart revolution. - Nicolas Verstaevel; Jérémy Boes; Marie-Pierre Gleizes (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI, 2017)

An Ontology Based Context-Aware Architecture for Smart Campus Applications. - Nicolas Verstaevel; Guillaume Garzone; Thierry Monteil 001; Nawal Guermouche; Johan Barthélemy; Pascal Perez (ISPA/IUCC/BDCloud/SocialCom/SustainCom, 2018)

Adaptation dynamique d'un drone aux perturbations environnementales par apprentissage (démonstration). - Bruno Dato; Nicolas Verstaevel; Frédéric Migeon; Marie-Pierre Gleizes (JFSMA, 2018)

A Self-Organized Learning Model for Anomalies Detection: Application to Elderly People. - Nicolas Verstaevel; Jean-Pierre Georgé; Carole Bernon; Marie-Pierre Gleizes (SASO, 2018)

Computer Vision and IoT-Based Sensors in Flood Monitoring and Mapping: A Systematic Review. - Bilal Arshad; Robert Ogie; Johan Barthélemy; Biswajeet Pradhan; Nicolas Verstaevel; Pascal Perez (Sensors, 2019)

Edge-Computing Video Analytics for Real-Time Traffic Monitoring in a Smart City. - Johan Barthélemy; Nicolas Verstaevel; Hugh I. Forehead; Pascal Perez (Sensors, 2019)

Combining Bandits and Lexical Analysis for Document Retrieval in a Juridical Corpora. - Filipo Studzinski Perotto; Nicolas Verstaevel; Imen Trabelsi 001; Laurent Vercouter (SGAI Conf., 2020)

Evaluating Correlations in IoT Sensors for Smart Buildings. - Davide Andrea Guastella; Nicolas Verstaevel; Cesare Valenti; Bilal Arshad; Johan Barthélemy (ICAART (1), 2021)

Exploration of Model Coupling Strategies in a Hybrid Agent-Based Traffic Simulation. - Jean-François Erdelyi; Frédéric Amblard; Benoit Gaudou; Elsy Kaddoum; Nicolas Verstaevel (MABS, 2021)

Deciding when to quit the gambler's ruin game with unknown probabilities. - Filipo Studzinski Perotto; Imen Trabelsi 001; Stéphanie Combettes; Valérie Camps; Nicolas Verstaevel (Int. J. Approx. Reason., 2021)

Cooperation-Based Search of Global Optima. - Damien Vergnet; Elsy Kaddoum; Nicolas Verstaevel; Frédéric Amblard (OLA, 2022)

How to Solve a Classification Problem Using a Cooperative Tiling Multi-agent System? - Thibault Fourez; Nicolas Verstaevel; Frédéric Migeon; Frédéric Schettini; Frédéric Amblard (PAAMS, 2022)

An ensemble Multi-Agent System for non-linear classification. - Thibault Fourez; Nicolas Verstaevel; Frédéric Migeon; Frédéric Schettini; Frédéric Amblard (CoRR, 2022)

TTC-SLSTM: Human Trajectory Prediction Using Time-to-Collision Interaction Energy. - Huu-Tu Dang; Raphael Korbmacher; Antoine Tordeux; Benoit Gaudou; Nicolas Verstaevel (KSE, 2023)

A Multi-level Density-Based Crowd Simulation Architecture. - Huu-Tu Dang; Benoit Gaudou; Nicolas Verstaevel (PAAMS, 2023)

Explicabilité et interprétabilité d'un système multi-agent ensembliste pour l'apprentissage supervisé. - Clément Blanco-Volle; Nicolas Verstaevel; Stéphanie Combettes; Michel Povlovitsch Seixas; Marie-Pierre Gleizes (JFSMA, 2024)

HyPedSim : Un framework pour la simulation multi-niveau de foules denses. - Huu-Tu Dang; Benoit Gaudou; Nicolas Verstaevel (JFSMA, 2024)

Explainability and Interpretability of an Ensemble Multi-agent System for Supervised Learning. - Clément Blanco-Volle; Nicolas Verstaevel; Stéphanie Combettes; Marie-Pierre Gleizes; Michel Povlovitsch Seixas (PRIMA, 2024)

A literature review of dense crowd simulation. - Huu-Tu Dang; Benoit Gaudou; Nicolas Verstaevel (Simul. Model. Pract. Theory, 2024)

HyPedSim: A Multi-Level Crowd-Simulation Framework - Methodology, Calibration, and Validation. - Huu-Tu Dang; Benoit Gaudou; Nicolas Verstaevel (Sensors, 2024)

Modèles de Substitution pour les Modèles à base d'Agents : Enjeux, Méthodes et Applications. - Paul Saves; Nicolas Verstaevel; Benoit Gaudou (CoRR, 2025)