Affiliation:
1. Stanford Research Institute, Menlo Park, California
Abstract
Our paper on the use of heuristic information in graph searching defined a path-finding algorithm, A*, and proved that it had two important properties. In the notation of the paper, we proved that if the heuristic function ñ (n) is a lower bound on the true minimal cost from node n to a goal node, then A* is <u>admissible;</u> i.e., it would find a minimal cost path if any path to a goal node existed. Further, we proved that if the heuristic function also satisfied something called the <u>consistency assumption,</u> then A* was <u>optimal;</u> i.e., it expanded no more nodes than any other admissible algorithm A no more informed than A*. These results were summarized in a book by one of us.
Publisher
Association for Computing Machinery (ACM)
Reference1 articles.
1. [fr1] Nils J. Nilsson Problem-Solving Methods in Artificial Intelligence McGraw-Hill Book Co. New York New York 1971. [fr1] Nils J. Nilsson Problem-Solving Methods in Artificial Intelligence McGraw-Hill Book Co. New York New York 1971.
Cited by
133 articles.
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