Proceedings Abstracts of the Twenty-Fifth International Joint Conference on Artificial Intelligence

On State-Dominance Criteria in Fork-Decoupled Search / 3265
álvaro Torralba, Daniel Gnad, Patrick Dubbert, Jörg Hoffmann

Fork-decoupled search is a recent approach to classical planning that exploits fork structures, where a single center component provides preconditions for several leaf components. The decoupled states in this search consist of a center state, along with a price for every leaf state. Given this, when does one decoupled state dominate another? Such state-dominance criteria can be used to prune dominated search states. Prior work has devised only a trivial criterion. We devise several more powerful criteria, show that they preserve optimality, and establish their interrelations. We show that they can yield exponential reductions. Experiments on IPC benchmarks attest to the possible practical benefits.