Adaptive and cooperative multi-agents systems

Our team, at a glance

(~ 24 researchers)

We aim at designing complex dynamic systems and self-adaptive systems with emerging functionalities. Our approach is based on self-organising multi-agent systems which prove very effective when considering heterogeneous and large-scale distributed systems in which non-linearities and changes are due to inner and outer dynamics. Our know-how finds application in AI, robotics, distributed systems, social simulations, local search optimization, user profiling, prediction tools, control of complex systems, decision support, just to name a few.


  • Agents for software architecture and system deployment
  • Adaptative multi-agent systems for multidisciplinary design optimization in aircraft design processes
  • Decision & negotiation through emotion & crisis
  • Autonomic protocol-based coordination in dynamic inter-organizational workflow
  • Parameter self-tuning for controlling complex dynamic systems such as car engines
  • Dynamic community detection to identify trends in user-generated contents (marketing & prediction, social networks analysis, community detection, metrics)
  • Self-organising multi-agent systems for users' profiling and behaviours learning in information and ambient systems
  • Agents for agricultural & water management strategies
  • energy consumption in buildings
  • bioprocesses etc.