Symbolic Search for Optimal Total-Order HTN Planning Article Swipe
Related Concepts
Heuristics
Task (project management)
Heuristic
Computer science
Order (exchange)
Mathematical optimization
Artificial intelligence
Machine learning
Theoretical computer science
Mathematics
Engineering
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Systems engineering
Finance
Gregor Behnke
,
David Speck
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v35i13.17396
· OA: W3175302475
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v35i13.17396
· OA: W3175302475
Symbolic 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.
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