Applying Monte-Carlo Tree Search in HTN Planning
| Autor: | Julia Wichlacz, Daniel Höller, Álvaro Torralba, Jörg Hoffmann |
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| Rok vydání: | 2021 |
| Zdroj: | Aalborg University |
| ISSN: | 2832-9163 2832-9171 |
| DOI: | 10.1609/socs.v11i1.18538 |
| Popis: | Search methods are useful in hierarchical task network (HTN) planning to make performance less dependent on the domain knowledge provided, and to minimize plan costs. Here we investigate Monte-Carlo tree search (MCTS) as a new algorithmic alternative in HTN planning. We implement combinations of MCTS with heuristic search in PANDA. We furthermore investigate MCTS in JSHOP, to address lifted (non-grounded) planning, leveraging the fact that, in contrast to other search methods, MCTS does not require a grounded task representation. Our new methods yield coverage performance on par with the state of the art, but in addition can effectively minimize plan cost over time. |
| Databáze: | OpenAIRE |
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