K* and Partial Order Reduction for Top-quality Planning

Michael Katz, Junkyu Lee

Keywords: classical planning, heuristic search, top-quality planning, partial order reduction

TL;DR: We exploit partial order reduction in K* for unordered top-quality planning, significantly improve over the current state of the art

Abstract: Partial order reduction techniques are successfully used for various settings in planning, such as classical planning with A* search or with decoupled search, fully-observable nondeterministic planning with LAO*, planning with resources, or even goal recognition design. Here, we continue this trend and show that partial order reduction can be used for top-quality planning with K* search. We discuss the possible pitfalls of using stubborn sets for top-quality planning and the guarantees provided. We perform an empirical evaluation that shows the proposed approach to significantly improve over the current state of the art in unordered top-quality planning.