Scheduling algorithms for improving the response in intelligent real-time environments

Over the last few years, the usefulness and maturity of artificial intelligence technologies, and in particular of knowledge-based systems, have been demonstrated by the ever growing number of commercial applications using them. In the domain of real-time control systems (process control, avionics, robotics, ...), these techniques have been considered with a renewed interest, as they appear as a promising approach to cope with the increasing complexity of the systems to be controlled. The integration of nonpredictable methods in real time systems is one of the crucial points. A task model allowing the representation of activities with optional parts and several scheduling algorithms to incorporate them into real time systems is described.