This project is an offspring of the project (see below).
It focuses on the design and the integration of local assistant agents, experts in viability analysis, decision, argumentation, negotiation, to help social actors/stakeholders/players
in participatory management of shared resources (socio-eco-systems).
See a recent description in
and a presentation in the - portal.
Recent funding was through: the Program PICS (Projets Internationaux de Coopération Scientifique), , 2017-2019
and the Centre de Développement Technologique, , & , 2019.
The objective is the definition and evaluation of a companion methodology
for a participative implementation and management of protected areas
(for biodiversity protection and social inclusion).
The methodology uses informatics: multi-agent participative simulation combining distributed role playing games and simulation of environmental resources.
Main funding has been through here.
This project is about the design of Internet of Things architectures for data and knowledge management, based on knowledge processing, agent and multi-agent, adaptation and machine learning (deep learning) techniques.
Recent funding has been through the ESMOCYP (Efficient Semantic MOdels and Fault-tolerant Middleware for CYber-Physical Systems) Project of PROBRAL international scientific cooperation program, 2016-2018.
The objective is to address fault-tolerance of distributed multi-agent cooperative applications.
We use both techniques of adaptive replication and of exception handling.
Main funding has been through the Sécurité et sûreté informatique french research program.
The goal of this project is to conceive and test a new architecture for a post-IP environment.
This post-IP architecture is mainly based on virtual networking with a piloting system able to cope
with the constraints.
This architecture is intelligence-oriented using mechanisms coming from Multi-Agent systems.
The reason of this new architecture comes from the limits of the current Internet architecture
in a large number of environments like wireless networks, sensor networks or RFID networks.
Main funding has been through the Future Networks Program.
The contributions of this project are, in order of relevance, the development of a context-and-location
aware framework for ubiquitous learning and collaboration applications,
the definition of a meta-description for defining context
and the development of efficient testing strategies for such systems.
Main funding has been through the STIC-AmSud Program.
Note: Between 2010 and 2015, I have stopped most of my involvements in research projects because of my full time position as Director of CNRS Brasil (Bureau CNRS Brésil).