@inproceedings{1b78e531a0d145f8b710cc859e7c26fb,
title = "Pattern database heuristics for fully observable nondeterministic planning",
abstract = "When planning in an uncertain environment, one is often interested in finding a contingent plan that prescribes appropriate actions for all possible states that may be encountered during the execution of the plan. We consider the problem of finding strong cyclic plans for fully observable nondeterministic (FOND) planning problems. The algorithm we choose is LAO*, an informed explicit state search algorithm. We investigate the use of pattern database (PDB) heuristics to guide LAO* towards goal states. To obtain a fully domain-independent planning system, we use an automatic pattern selection procedure that performs local search in the space of pattern collections. The evaluation of our system on the FOND benchmarks of the Uncertainty Part of the International Planning Competition 2008 shows that our approach is competitive with symbolic regression search in terms of problem coverage, speed, and plan quality.",
author = "Robert Mattm{\"u}ller and Manuela Ortlieb and Malte Helmert and Pascal Bercher",
year = "2010",
month = may,
day = "5",
doi = "10.1609/icaps.v20i1.13408",
language = "English",
isbn = "978-1-57735-449-9",
volume = "20",
series = "International Conference on Automated Planning and Scheduling",
publisher = "AAAI Press",
pages = "105--112",
editor = "Ronen Brafman and H{\'e}ctor Geffner and J{\"o}rg Hoffmann and Henry Kautz",
booktitle = "Proceedings of the Twentieth International Conference on Automated Planning and Scheduling",
note = "20th International Conference on Automated Planning and Scheduling, ICAPS 2010 ; Conference date: 12-05-2010 Through 16-05-2010",
}