Downward Path Preserving State Space Abstractions (Extended Abstract)

Zilles, Sandra (University of Regina) | Holte, Robert C. (University of Alberta)

AAAI Conferences 

A problem that often arises in using abstraction is the generation of abstract states, called spurious states, that are—in the abstract space—reachable from some abstract image of a state s, but which have no corresponding state in the original space reachable from s. Spurious states can have a negative effect on pattern database sizes and heuristic quality. We formally define a property—the downward path preserving property (DPP)—that guarantees an abstraction has no spurious states. Analyzing the computational complexity of (i) testing the DPP property for a given state space and abstraction and of (ii) determining whether this property is achievable at all for a given state space, results in strong hardness theorems. On the positive side, we identify formal conditions under which finding DPP abstractions is tractable.

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