The Compression Power of Symbolic Pattern Databases

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The Compression Power of Symbolic Pattern Databases
The heuristics used for planning and search often take the pattern databases generated from abstracted versions of the given state space. Pattern databases are typically stored p tables with one entry for each state in the abstract hich limits the size of the abstract state space and therefore the quality of the heuristic that can be used with a given amount of memory. In the AIPS-2002 conference Stefan Edelkamp introduced an alternative representation, called symbolic pattern databases, which, for the Blocks World, required two orders of magnitude less memory than a lookup table to store a pattern database. This paper presents experimental evidence that Edelkamp's result is not restricted to a single domain. Symbolic pattern databases, in the form of Algebraic Decision Diagrams, are one or more orders of magnitude smaller than lookup tables on a wide variety of problem and abstractions.
Marcel Ball, Robert C. Holte
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2008
Where AIPS
Authors Marcel Ball, Robert C. Holte
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