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Issue No. 07 - July (1994 vol. 16)
ISSN: 0162-8828
pp: 701-710
<p>Iterative-deepening searches mimic a breadth-first node expansion with a series of depth-first searches that operate with successively extended search horizons. They have been proposed as a simple way to reduce the space complexity of best-first searches like A* from exponential to linear in the search depth. But there is more to iterative-deepening than just a reduction of storage space. As the authors show, the search efficiency can be greatly improved by exploiting previously gained node information. The information management techniques considered here owe much to their counterparts from the domain of two-player games, namely the use of fast-execution memory functions to guide the search. The authors' methods not only save node expansions, but are also faster and easier to implement than previous proposals.</p>
computational complexity; search problems; game theory; iterative methods; iterative-deepening search; breadth-first node expansion; depth-first searches; successively extended search horizons; space complexity; best-first searches; A* search; search efficiency; information management techniques; two-player games; fast-execution memory functions

A. Reinefeld and T. Marsland, "Enhanced Iterative-Deepening Search," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 16, no. , pp. 701-710, 1994.
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