Complexity results for HTN planning | Zendy

Kutluhan Erol | Zendy; James Hendler | Zendy; Dana S. Nau | Zendy

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Complexity results for HTN planning

Author(s) -

Kutluhan Erol,

James Hendler,

Dana S. Nau

Publication year - 1996

Publication title -

annals of mathematics and artificial intelligence

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.369

H-Index - 55

eISSN - 1573-7470

pISSN - 1012-2443

DOI - 10.1007/bf02136175

Subject(s) - task (project management) , computer science , decomposition , work (physics) , artificial intelligence , complex system , machine learning , engineering , systems engineering , mechanical engineering , ecology , biology

Most practical work on AI planning systems during the last fifteen years has beenbased on hierarchical task network (HTN) decomposition, but until now, there has beenvery little analytical work on the properties of HTN planners. This paper describes howthe complexity of HTN planning varies with various conditions on the task networks,and how it compares to STRIPS-style planning.1 IntroductionIn AI planning research, planning practice (as embodied in implemented planning systems)tends to ...

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