Custom-Design of FDR Encodings: The Case of Red-Black Planning

Daniel Fišer, Daniel Gnad, Michael Katz, Joerg Hoffmann

Keywords: FDR, mutex, mutex group, red-black

Abstract:

Classical planning tasks are commonly described in PDDL, while most planning
systems operate on a grounded finite-domain representation (FDR). The
translation of PDDL into FDR is complex and has a lot of choice points---it
involves identifying so called mutex groups---but most systems rely on the
translator that comes with Fast Downward. Yet the translation choice points can
strongly impact performance. Prior work has considered optimizing FDR encodings
in terms of the number of variables produced. Here we go one step further by
proposing to custom-design FDR encodings, optimizing the encoding to suit
particular planning techniques. We develop such a custom design here for
red-black planning, a partial delete relaxation technique. The FDR encoding
affects the causal graph and the domain transition graph structures, which
govern the tractable fragment of red-black planning and hence affects the
respective heuristic function. We develop integer linear programming techniques
optimizing the scope of that fragment in the resulting FDR encoding. We
empirically show that the performance of red-black planning can be improved
through such FDR custom design.