%0 Journal Article %A Jensen, Rune M. %A Veloso, Manuela M. %A Bryant, Randal %D 2003 %T Guided Symbolic Universal Planning %U https://kilthub.cmu.edu/articles/journal_contribution/Guided_Symbolic_Universal_Planning/6622415 %R 10.1184/R1/6622415.v1 %2 http://www-2.cs.cmu.edu/~bryant/pubs.html %K Software Research %X

Symbolic universal planning based on the reduced Ordered Binary Decision Diagram (OBDD) has been shown to be an efficient approach for planning in non-deterministic domains. To date, however, no guided algorithms exist for synthesizing universal plans. In this paper, we introduce a general approach for guiding universal planning based on an existing method for heuristic symbolic search in deterministic domains. We present three new sound and complete algorithms for best-first strong, strong cyclic, and weak universal planning. Our experimental results show that guiding the search dramatically can reduce both the computation time and the size of the generated plans.

%I Carnegie Mellon University