Hybrid Systems and AI: Modeling Analysis and Control of Discrete Plus Continuous Systems
Papers from the AAAI Spring Symposium
Gautam Biswas and Sheila McIlraith,Cochairs
The use of digital computers to control continuous, dynamic processes has led to the development of hybrid(discrete + continuous) systems. The cross-disciplinary hybrid systems community combines discrete event and continuous systems modeling techniques with control theory for analysis and verification of embedded systems and synthesis of controller actions. Hybrid behavior is generally described as intervals of piecewise continuous behaviors (modes) interspersed with discrete transitions (mode transitions) that occur at points in time. Examples of hybrid systems include robots, air traffic control systems, chemical plants, autonomous spacecraft control, smart buildings and automated multi-vehicle highway systems. The growing field of hybrid systems has seen a great deal of activity in the last few years often focusing on synthesis, verification and stability analysis of controllers for hybrid systems. Interestingly, a number of the problems addressed by this community are shared by AI researchers studying robotics, planning, simulation, verification, execution monitoring, decision analysis, reasoninabout action, diagnosis, modeling and analysis of physical systems, and perception. This symposium aims to bring together these different communities to explore opportunities for exploiting AI representation and reasoning techniques for hybrid system modeling and analysis, and for integrating techniques from hybrid systems into current AI research.