Tracking Branches in Trees - A Propositional Encoding for Solving Partially-Ordered HTN Planning Problems

被引:6
|
作者
Behnke, Gregor [1 ]
Hoeller, Daniel [1 ]
Biundo, Susanne [1 ]
机构
[1] Ulm Univ, Inst Artificial Intelligence, Ulm, Germany
关键词
planning; hierarchical planning; SAT;
D O I
10.1109/ICTAI.2018.00022
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Planning via SAT has proven to be an efficient and versatile planning technique. Its declarative nature allows for an easy integration of additional constraints and can harness the progress made in the SAT community without the need to adapt the planner. However, there has been only little attention to SAT planning for hierarchical domains. To ease encoding, existing approaches for HTN planning require additional assumptions, like non-recursiveness or totally-ordered methods. Both limit the expressiveness of HTN planning severely. We propose the first propositional encodings which are able to solve general, i.e., partially-ordered, HTN planning problems, based on a previous encoding for totally-ordered problems. The empirical evaluation of our encoding shows that it outperforms existing HTN planners significantly.
引用
收藏
页码:73 / 80
页数:8
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