As intelligent, autonomous systems are embedded in critical real-world environments, it becomes increasingly important to rigorously characterize how these systems will perform. Research i n real-time computing and control has developed ways of proving that a given control system will meet the demands of an environment, but has not addressed the dynamic planning of control actions. Building an agent that can exibly achieve its goals in changing environments requires a blending of real-time computing and AI technologies. The Cooperative I n telligent Real-time Control Architecture (CIRCA) implements this blending by executing complex AI methods and guaranteed real-time control plans on separate subsystems. We describe the formal model of agent/environment interactions that CIRCA uses to build control plans, and we s h o w h o w those control plans are guaranteed to meet domain requirements. CIRCA's world model provides the information required to make real-time performance guarantees, but avoids unnecessary complexity.
Their approach is implemented upon CIRCA, an intelligent real-time control architecture that combines AI planning techniques to meet the demands in a dynamic real-time computing and control environment REF .
World Modeling for the Dynamic Construction of Real � Time Control Plans
Artif. Intell.
Artif. Intell.
Mathematics Computer Science