HTN Problem Spaces: Structure, Algorithms, Termination
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Published:2021-08-20
Issue:1
Volume:3
Page:2-9
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ISSN:2832-9163
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Container-title:Proceedings of the International Symposium on Combinatorial Search
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language:
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Short-container-title:SOCS
Author:
Alford Ron,Shivashankar Vikas,Kuter Ugur,Nau Dana
Abstract
For HTN planning, we formally characterize and classify four kinds of problem spaces in which each node represents a planning problem or subproblem. Two of the problem spaces are searched by current HTN planning algorithms; the other two problem spaces are new.This enables us to provide:Sufficient (and in one case, necessary) conditions for finiteness of each kind of problem space. The conditions can be evaluated up-front to see if an HTN planning problem is finite.Loop-detection tests that can be used in HTN planners to ensure termination when the problem space is finite.A way to compute the correct value for an upper-bound parameter in an HTN-to-PDDL translation algorithm published in IJCAI-2009.Planning algorithms that utilize the two new problem spaces to guarantee termination on broader classes of planning problems than previous HTN planning algorithms.
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Cited by
1 articles.
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