Hybrid Planning for Partially Hierarchical Domains
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. 1 Introduction Traditionally, classical planning probl...
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Text
Kambhampati et al. "Hybrid Planning for Partially Hierarchical Domains." AAAI Conference on Artificial Intelligence, 1998.Markdown
[Kambhampati et al. "Hybrid Planning for Partially Hierarchical Domains." AAAI Conference on Artificial Intelligence, 1998.](https://mlanthology.org/aaai/1998/kambhampati1998aaai-hybrid/)BibTeX
@inproceedings{kambhampati1998aaai-hybrid,
title = {{Hybrid Planning for Partially Hierarchical Domains}},
author = {Kambhampati, Subbarao and Mali, Amol Dattatraya and Srivastava, Biplav},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {1998},
pages = {882-888},
url = {https://mlanthology.org/aaai/1998/kambhampati1998aaai-hybrid/}
}