A study of a dynamic progressive reasoning system
Abdel‐Illah Mouaddib · Journal of Experimental & Theoretical Artificial Intelligence · 2000
Controlling resource-bounded systems not only involves taking decisions about planning and scheduling reasoning components to achieve time-constrained goals, but also about how to monitor the progress of these components. We propose an extended closed-loop planning, scheduling and execution. This extended closed-loop allows one to address the following limitations: (1) dynamic and time-constrained environments, (2) uncertainty regarding the duration of reasoning components and (3) tolerance to execution failure. The interactions in the extended closed-loop allow one: first to revise the current schedule when deviations from a predetermined schedule occur during execution, second to update continuously the set of goals on which the control focuses its decision and third how this set of goals is updated when an execution failure occurs. We discuss these issues in a progressive reasoning system implemented and applied to a railway control application where real-time (dynamic and time-constrained) situations occur.