Linear programming for heuristics in optimal planning

Many recent planning heuristics are based on LP optimization. However, planning experts mostly use LP solvers as a black box and it is often not obvious to them which LP techniques would be most suitable for their specific applications. To foster the communication between the planning and the optimization community, this paper gives an easily accessible overview over these recent LP-based heuristics, namely the optimal cost partitioning heuristic for abstractions, the post-hoc optimization heuristic, a landmark heuristic, the state-equation heuristic, and a delete relaxation heuristic. All these heuristics fit the framework of so-called operator-counting constraints, which we also present.