Abstract
This paper examines the possibility of removing redundant information from a given
knowledge base and restructuring it in the form of a tree to enable efficient
problemsolving routines. We offer a novel approach that guarantees removal of all redundancies
that hide a tree structure. We develop a polynomial-time algorithm that, given an
arbitrary binary constraint network, either extracts (by edge removal) a precise tree
representation from the path-consistent version of the network or acknowledges that
no such tree can be extracted. In the the latter case, a tree is generated that may serve
as an approximation to the original network.
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