Abstract
Hierarchical task network and action-based planning approaches have traditionally been studied separately. In many domains, human expertise in the form of hierarchical reduction schemas exists, but is incomplete. In such domains, hybrid approaches that use both HTN and action-based planning techniques are needed. In this paper, we extend our previous work on refinement planning to include hierarchical planning. Specifically, we provide a generalized plan-space refinement that is capable of handling non-primitive actions. The generalization provides a principled way of handling partially hierarchical domains, while preserving systematicity, and respecting the user-intent inherent in the reduction schemas. Our general account also puts into perspective the many surface differences between the HTN and action-based planners, and could support the transfer of progress between HTN and action-based planning approaches.
Original language | English (US) |
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Title of host publication | Proceedings of the National Conference on Artificial Intelligence |
Editors | Anon |
Place of Publication | Menlo Park, CA, United States |
Publisher | AAAI |
Pages | 882-888 |
Number of pages | 7 |
State | Published - 1998 |
Event | Proceedings of the 1998 15th National Conference on Artificial Intelligence, AAAI - Madison, WI, USA Duration: Jul 26 1998 → Jul 30 1998 |
Other
Other | Proceedings of the 1998 15th National Conference on Artificial Intelligence, AAAI |
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City | Madison, WI, USA |
Period | 7/26/98 → 7/30/98 |
ASJC Scopus subject areas
- Software