Planning with Multi-Valued Landmarks

Lei Zhang, Chong-Jun Wang, Jun Wu, Meilin Liu, Jun-Yuan Xie

Abstract: Landmark heuristics are perhaps the most accurate current known admissible heuristics for optimal planning. A disjunctive action landmark can be seen a form of at-least-one constraint on the actions it contains. In many domains, some critical propositions have to be established for a number of times. Propositional landmarks are too weak to express this kind of constraints. In this paper, we propose to generalize landmarks to multi-valued landmarks to represent the more general cardinality constraints. We present a class of local multi-valued landmarks that can be efficiently extracted from propositional landmarks. By encoding multi-valued landmarks into CNF formulas, we can also use SAT solvers to systematically extract multivalued landmarks. Experiment evaluations show that multivalued landmark based heuristics are more close to h* and compete favorably with the state-of-the-art of admissible landmark heuristics on benchmark domains.