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On hierarchical task networks. (English) Zbl 06658186
Michael, Loizos (ed.) et al., Logics in artificial intelligence. 15th European conference, JELIA 2016, Larnaca, Cyprus, November 9–11, 2016. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 10021, 551-557 (2016).
Summary: In planning based on hierarchical task networks (HTN), plans are generated by refining high-level actions (“compound tasks”) into lower-level actions, until primitive actions are obtained that can be sent to execution. While a primitive action is defined by its precondition and effects, a high-level action is defined by zero, one or several methods: sets of (high-level or primitive) actions decomposing it together with a constraint. We give a semantics of HTNs in terms of dynamic logic with program inclusion. We propose postulates guaranteeing soundness and completeness of action refinement. We also show that hybrid planning can be analysed in the same dynamic logic framework.
For the entire collection see [Zbl 1350.68015].

MSC:
68T27 Logic in artificial intelligence
Software:
ConGolog
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