Beyond Red-Black Planning: Limited-Memory State Variables
Speicher, Patrick (Saarland University) | Steinmetz, Marcel (Saarland University) | Gnad, Daniel (Saarland University) | Hoffmann, Jörg (Saarland University) | Gerevini, Alfonso (University of Brescia)
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.
Jun-14-2017
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