A Robust Heuristic for the Multidimensional A-star/Wavefront Hybrid Planning Algorithm
Automated planning using heuristic search or gradient algorithms is a feasible method for solving many planning problems. However, if planning is performed for several (possibly colliding) entities, the size of the state space increases dramatically. If these entities have limited predictability, observability or controllability, a single plan can no longer suffice, and robust multi-variant planning is no longer feasible due to scale. This paper presents the A-star/Wavefront hybrid planning algorithm and proposes a new heuristic for selection of its deviation zones.
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