Beyond Red-Black Planning: Limited-Memory State Variables
Patrick Speicher, Marcel Steinmetz, Daniel Gnad, Jörg Hoffmann, Alfonso Gerevini · Proceedings of the International Conference on Automated Planning and Scheduling · 2017
Red-black planning delete-relaxes only some of the state variables. This is coarse-grained in that, for each variable, it either remembers all past values (red), or remembers only the most recent one (black). We herein introduce limited-memory state variables, that remember a subset of their most recent values. It turns out that planning is still PSPACE-complete even when the memory is large enough to store all but a single value. Nevertheless, limited memory can be used to substantially broaden a known tractable fragment of red-black planning, yielding better heuristic functions in some domains.