@InProceedings{ bercher09solving,
  author    = "Pascal Bercher and Robert Mattm{\"u}ller",
  title     = "Solving Non-deterministic Planning Problems with Pattern Database Heuristics",
  booktitle = "Proceedings of the 32nd Annual Conference on Artificial Intelligence (KI 2009)",
  pages     = "57--64",
  year      = "2009",
  subproject={S1},
  access={restricted},
  bibtex={bercher.ki09.bib},
  pdf={bercher.ki09.pdf},
  abstract={Non-determinism arises naturally in many real-world applications of
            action planning. Strong plans for this type of problems can be found
            using AO* search guided by an appropriate heuristic function. Most
            domain-independent heuristics considered in this context so far are
            based on the idea of ignoring delete lists and do not properly take
            the non-determinism into account. Therefore, we investigate the
            applicability of pattern database (PDB) heuristics to
            non-deterministic planning. PDB heuristics have emerged as rather
            informative in a deterministic context. Our empirical results suggest
            that PDB heuristics can also perform reasonably well in
            non-deterministic planning. Additionally, we present a generalization
            of the pattern additivity criterion known from classical planning to
            the non-deterministic setting.},
}