Anytime heuristic search in temporal HTN planning for developing incident action plans

Extreme events challenge emergency managers' decision making capabilities of developing unified action plans to ensure effective coordination for multiple responding agencies. In this paper, we present a novel HTN planner, called XEPlanner, aimed at working in dynamic emergency response environment with critical time constraints. By understanding incident action plans developing process and characteristics of flood controlling, this paper proposes a set of planning requirements as the guidance for designing a domain specific HTN planner, which challenge the current known HTN planners. Based on the classical AI planning technologies, our planner is designed and implemented for adapting to the application domain. It follows the anytime principles: the first feasible plan can be quickly produced and the quality of the plans is improved as more time is available. Additionally, a set of heuristics for selecting search nodes is proposed for taking into account preferences of emergency managers during the planning process. Moreover, the priorities of incident objectives can be handled effectively. Our experimental results demonstrate that our planner satisfies all the proposed planning requirements and has advantages when it's applied in flood evacuation domain.