The degree to which a planner succeeds and meets response deadlines depends on the correctness and completenessof its modelswhichdescribe events and actions that change the world state. It is often unrealistic to expect perfect models,so a planner must be able to detect and respond to states it had not planned to handle. In this paper, we characterize different classes of these "unhandled" states and describe planning algorithms to build tests for, and later respond to them. Wehave implemented these unhandledstate detection and response algorithms in the Cooperative Intelligent Real-time Control Architecture (CIRCA),which combinesan AI planner with a separate real-time system so that plans me built, scheduled, and then executed with real-time guarantees. Test results from flight simulation show the newalgorithmenables a fully-automatedaircraft to react appropriately to certain classes of unhandled states, averting failure and giving the aircraft a new chance to achieve its g...
Ella M. Atkins, Edmund H. Durfee, Kang G. Shin