Decoupled Strong Stubborn Sets

Gnad, Daniel and Wehrle, Martin and Hoffmann, Jörg. (2016) Decoupled Strong Stubborn Sets. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), 4. Palo Alto, California, pp. 3110-3116.

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Official URL: http://edoc.unibas.ch/45240/

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Recent work has introduced fork-decoupled search , addressing classical planning problems where a single center component provides preconditions for several leaf components. Given a fixed center path ⇡ C , the leaf moves compliant with ⇡ C can then be scheduled independently for each leaf. Fork- decoupled search thus searches over center paths only, maintaining the compliant paths for each leaf separately. This can yield dramatic benefits. It is empirically complementary to partial order reduction via strong stubborn sets, in that each method yields its strongest reductions in different bench- marks. Here we show that the two methods can be combined, in the form of strong stubborn sets for fork-decoupled search. This can yield exponential advantages relative to both methods. Empiri- cally, the combination reliably inherits the best of its components, and often outperforms both.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Artificial Intelligence (Helmert)
UniBasel Contributors:Wehrle, Martin
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Publisher:AAAI Press
Note:Publication type according to Uni Basel Research Database: Conference paper
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Last Modified:27 Nov 2018 14:17
Deposited On:11 Oct 2017 10:29

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