The team research lines are the following:

• Diagnosis and decision-making - Model based approaches
  
• Monitoring and Supervision based on learning and pattern recognition approaches
  
• Optimisation and supervisory control of non linear systems

The DISCO team develops diagnosis and supervision tools for complex dynamic systems, possibly including human operators. We do stress the qualitative nature of the data that is relevant to supervision in resonance with the continuous aspects of the systems.  Hence, hybrid systems and the interface between continuous signals and their interpretation in terms of discrete events are at the core of our activities. The qualitative nature of knowledge and the uncertainties tainting the data induce us to call on qualitative and symbolic formalisms originated from Artificial Intelligence as well as on machine learning and pattern recognition methods.