Ia survey of research in distributed, continual planning

Complex, real-world domains require rethinking traditional approaches to AI planning. Planning and executing the resulting plans in a dynamic environm ent implies a continual approach in which planning and execution are interl eaved, uncertainty in the current and projected world state is recognized a nd handled appropriately, and replanning can be performed when the situatio n changes or planned actions fail. Furthermore, complex planning and execut ion problems may require multiple computational agents and human planners t o collaborate on a solution. In this article, we describe a new paradigm fo r planning in complex, dynamic environments, which we term distributed, con tinual planning (DCP). We argue that developing DCP systems will be necessa ry for planning applications to be successful in these environments. We giv e a historical overview of research leading to the current state of the art in DCP and describe research in distributed and continual planning.