Applied Mathematics & Information Sciences

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This work is concerned with how to improve the efficiency of heuristic search in a planning system. Utilize the dependency relations between the variables in a goal, a subgoal ordering method is first used to guide the heuristic search in a more reasonable way. The idea of helpful value in a goal is then introduced. A more accurate heuristic cost can be achieved by using the helpful value when we compute the heuristic cost. Finally, a heuristic algorithm combined subgoal ordering with helpful value is proposed. The algorithm is implemented in the planning system Fast Downward. The experimental results show the efficiency of the proposed heuristic search algorithm on the benchmarks of International Planning Competitions (IPC) 2008.

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