World Modeling for the Dynamic Construction of Real-Time Control Plans

As intelligent autonomous systems are embedded in critical real world environments it becomes increasingly important to rigorously characterize how these systems will perform Research in 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 Intelligent 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 show how 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 To appear in AI Journal The work reported in this paper was supported in part by the National Science Foundation under Grants IRI and IRI by a NSF Graduate Fellowship by the O ce of Naval Research under Grant N J and by the Arpa Rome Laboratory Planning Initiative F C The opinions ndings and recommendations expressed in this publication are those of the authors and do not necessarily re ect the views of the funding agencies This paper was written when David Musliner was a graduate student at the University of Michigan Ann Arbor Dr Musliner is currently also a liated with the University of Maryland Institute for Systems Research NSF Grant NSFD CDR