A method is described for efficient search of solution paths in artificial intelligence problems. The method's effects on total search efforts and resulting solution paths are analyzed. The method limits the depth of a growing search tree and the maximum number of expanding nodes. Classical uniform-cost search is modified by this method to be applicable to a planning problem for loading bridge assignments.
|Number of pages||5|
|Publication status||Published - 1987 Dec 1|
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