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A novel hierarchical task network planning approach for multi-objective optimization
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AI
DOI：10.1016/j.eswa.2024.124058.png)
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Abstract
En 中文
In this paper, we focus on how to generate the multi-objective optimal plan in hierarchical task network (HTN) planning. Many practical HTN planning problems not only require feasible plans, but also require these plans to achieve the best performance on multiple criteria, which is the multi-objective optimization problem in HTN planning. Aiming to generate the multi-objective optimal plan in HTN planning, a novel HTN planning approach is proposed. Our initial step is to express multiple criteria by extending the concept of the HTN planning domain. The primary search process of our proposed HTN planning approach has two components. The first one is heuristic search, which assesses the quality of methods/operators and organizes them according to their dominance relations. The second one is anytime search, which reduces the search space on the basis of the dominance relations between the partial plan and the non-dominated plan set, which is updated during the planning process. After the termination of the HTN planning search, a non-dominated plan set is returned for the decision-maker to choose from. We adopt Zeno Travel domain problems and an emergency evacuation planning problem in an experimental study to demonstrate how effective and practicable the proposed approach is.
Keywords:
HTN planning
Multiple objectives optimization
Dominance relations
Heuristic search
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W