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• W2158458082 abstract "Many AI problems can be recast as finding an optimal path in a discrete state space. An abstraction defines an admissible heuristic function as the distances in a smaller state space where arbitrary sets of states are aggregated into single states. A special case are pattern database (PDB) heuristics, which aggregate states if they agree on the state variables inside the pattern. Explicit-state abstraction is more flexible, explicitly aggregating selected pairs of states in a process that interleaves composition of abstractions with abstraction of the composites. The increased flexibility gains expressive power: sometimes, the real cost function can be represented concisely as an explicit-state abstraction, but not as a PDB. Explicit-state abstraction has been applied to planning and model checking, with highly promiSing empirical results." @default.
• W2158458082 created "2016-06-24" @default.
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• W2158458082 date "2008-07-13" @default.
• W2158458082 modified "2023-10-18" @default.
• W2158458082 title "Explicit-state abstraction: a new method for generating heuristic functions" @default.
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