Interleaving Deliberative and Reactive Planning in Dynamic Multi-Agent Domains

Reactive planning, consisting of pre-deened sensor-action rules, is well suited to eeectively respond to dynamic changes in real-time environments. However , it is in general challenging to strategically reason about long or short-term objectives using reac-tive planning. Therefore, ideally, deliberative and reactive planning should be integrated. In this paper , we introduce an adaptive interleaving of de-liberative and reactive planning as our approach for dealing with real-time dynamic environments. Two main aspects are responsible for the success of the approach. First, the deliberative planner uses depth-bounded forward chaining guided by goal-based heuristics. Second, the real-time state space is discretized as a function of the average time that the deliberative planner needs to generate a plan. This ensures that the state, as seen by the delib-erative planner, does not change in average while the plan is being generated. When a plan fails or a new plan is needed, the reactive planner takes over. We extend our approach to multi-agent real-time domains, where the need for collaborative deliber-ative planning is particularly needed. We implemented and demonstrate our integration using the Prodigy deliberative planner and the RoboCup soccer simulator server.