Stubborn Sets for Fully Observable Nondeterministic Planning

Abstract

Pruning techniques based on strong stubborn sets have recently shown their potential for SAS+ planning as heuristic search. Strong stubborn sets exploit operator independency to safely prune the search space. Like SAS+ planning, fully observable nondeterministic (FOND) planning faces the state explosion problem. However, it is unclear how stubborn set techniques carry over to the nondeterministics setting. In this paper, we introduce stubborn set pruning to FOND planning. We lift the notion of strong stubborn sets and introduce the conceptually more powerful notion of weak stubborn sets to FOND planning. Our experimental analysis shows that weak stubborn sets are beneficial to an LAO* search, and in particular show favorable performance when combined with symmetries and active operator pruning.