Abstract
Using abstract operators for least commitment in planning has been shown to potentially reduce the search space by an exponential factor. However a naive application of these operators can result in an unbounded growth in search space for the worst case. In this paper we investigate another important aspect of abstract operators - that of their construction. Similar to their application, naive construction of an abstract operator may leave you with little search space reduction even in the best case, and significant penalties in the worst. We explain what it means to be a good abstract operator and describe a method of creating good abstract operators. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Teutenberg, J., & Barley, M. (2005). Creating better abstract operators. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3607 LNAI, pp. 206–217). Springer Verlag. https://doi.org/10.1007/11527862_15
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