Solving Classical AI Planning Problems Using Planning-Independent CP Modeling and Search
| Autor: | Behrouz Babaki, Gilles Pesant, Claude-Guy Quimper |
|---|---|
| Rok vydání: | 2021 |
| Zdroj: | Proceedings of the International Symposium on Combinatorial Search. 11:2-10 |
| ISSN: | 2832-9163 2832-9171 |
| DOI: | 10.1609/socs.v11i1.18529 |
| Popis: | The combinatorial problems that constraint programming typically solves belong to the class of NP-hard problems. The AI planning community focuses on even harder problems: for example, classical planning is PSPACE-hard. A natural and well-known constraint programming approach to classical planning solves a succession of fixed plan-length problems, but with limited success. We revisit this approach in light of recent progress on general-purpose branching heuristics. We conduct an empirical comparison of our proposal against state-of-the-art planners. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|