Symbolic Search for Optimal Total-Order HTN Planning
AbstractSymbolic search has proven to be a useful approach to optimal classical planning. In Hierarchical Task Network (HTN) planning, however, there is little work on optimal planning. One reason for this is that in HTN planning, most algorithms are based on heuristic search, and admissible heuristics have to incorporate the structure of the task network in order to be informative. In this paper, we present a novel approach to optimal (totally-ordered) HTN planning, which is based on symbolic search. An empirical analysis shows that our symbolic approach outperforms the current state of the art for optimal totally-ordered HTN planning.
How to Cite
Behnke, G., & Speck, D. (2021). Symbolic Search for Optimal Total-Order HTN Planning. Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 11744-11754. https://doi.org/10.1609/aaai.v35i13.17396
AAAI Technical Track on Planning, Routing, and Scheduling