LMC RMM RM ’ s SOC MQ LMC RMM RM ’ s SOC MQ Simulator Other Agents

Many current and potential AI applications are intended to operate in dynamic environments, including those with multiple agents. As a result, standard AI plan-generation technology must be augmented with mechanisms for managing changing information, for fo-cusing attention when multiple events occur, and for coordinating with other planning processes. The DI-PART testbed (Distributed, Interactive Planner's Assistant for Real-time Transportation planning) was developed to serve as an experimental platform for analyzing a variety of such mechanisms. In this paper, we present an overview both of the DIPART system and of some of the methods for planning in dynamic environments that we have been investigating using DIPART. Many of these methods derive from theoretical work in real-time AI and in related elds, such as real-time operating systems.