Iterative-Expansion A
نویسندگان
چکیده
In this paper we describe an improvement to the popular IDA* search algorithm that emphasizes a different spacefor-time trade-off than previously suggested. In particular, our algorithm, called Iterative-Expansion A* (IEA*), focuses on reducing redundant node expansions within individual depth-first search (DFS) iterations of IDA* by employing a relatively small amount of available memory— bounded by the error in the heuristic—to store selected nodes. The additional memory required is exponential not in the solution depth, but only in the difference between the solution depth and the estimated solution depth. A constanttime hash set lookup can then be used to prune entire subtrees as DFS proceeds. Overall, we show 2to 26-fold time speedups vs. an optimized version of IDA* across several domains, and compare IEA* with several other competing approaches. We also sketch proofs of optimality and completeness for IEA*, and note that IEA* is particularly efficient for solving implicitly-defined general graph search problems.
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