Structural Symmetries for Fully Observable Nondeterministic Planning

Winterer, Dominik and Wehrle, Martin and Katz, Michael. (2016) Structural Symmetries for Fully Observable Nondeterministic Planning. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016), 4. Palo Alto, California, pp. 3293-3299.

PDF - Published Version

Official URL: http://edoc.unibas.ch/45239/

Downloads: Statistics Overview


Symmetry reduction has significantly contributed to the success of classical planning as heuristic search. However, it is an open question if symmetry reduction techniques can be lifted to fully observable nondeterministic (FOND) planning. We generalize the concepts of structural symmetries and symmetry reduction to FOND planning and specifically to the LAO* algorithm. Our base implementation of LAO* in the Fast Downward planner is competitive with the LAO*-based FOND planner myND. Our experiments further show that symmetry reduction can yield strong performance gains compared to our base implementation of LAO*.
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
Related URLs:
edoc DOI:
Last Modified:27 Nov 2018 14:44
Deposited On:11 Oct 2017 10:29

Repository Staff Only: item control page