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PSVN: A Vector Representation for Production Systems

In this paper we present a production system which acts on fixed length vectors of labels. Our goal is to automatically generate heuristics to search the state space for shortest paths between states efficiently. The heuristic values which guide search in the state space are obtained by searching for the shortest path in an abstract space derived from the definition of the original space. In PSVN, a state is a fixed length vector of labels and abstrac­ tions are generated by simply mapping the set of labels to another smaller set of labels (domain abstraction). A domain abstraction on labels in­ duces a state space abstraction and this abstract space preserves important properties of the origi­ nal space while usually being significantly smaller in size. It is guaranteed that the shortest path between two states in the original space is at least as long as the shortest path between their images in the abstract space. Hence, such abstractions provide admissible heuristics for search algorithms such as A* and IDA*. The mapping of states and operators can be efficiently obtained by applying the domain map on the labels. We explore im­ portant properties of state spaces defined in PSVN and abstractions generated by domain maps. De­ spite its simplicity, PSVN is capable to define all finitely generated permutation groups and such benchmark problems as Rubik's Cube, the sliding­ tile puzzles and the Blocks World.

Citation

I. Hernadvolgyi, R. Holte. "PSVN: A Vector Representation for Production Systems". Technical Report, April 2004.

Keywords: PSVN
Category: Technical Report

BibTeX

@manual{Hernadvolgyi+Holte:04,
  author = {Istvan Hernadvolgyi and Robert Holte},
  title = {PSVN: A Vector Representation for Production Systems},
  year = 2004,
}

Last Updated: March 14, 2007
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