BDDRPA: An Efficient BDD-Based Incremental Heuristic Search Algorithm for Replanning
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Xu, Yanyan
Su, Kaile
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Abdul Sattar and Byeong-Ho Kang
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Hobart
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Abstract
We introduce a new algorithm, BDDRPA*, which is an efficient BDD-based incremental heuristic search algorithm for replanning. BDDRPA* combines the incremental heuristic search with BDD-based search to efficiently solve replanning search problems in artificial intelligence. We do a lot of experiments and our experiment evaluation proves BDDRPA* to be a powerful incremental search algorithm. BDDRPA* outperforms breadth-first search by several orders of magnitude for huge size search problems. When the changes to the search problems are small, BDDRPA* needs less runtime by reusing previous information, and even when the changes reach to 20 percent of the size of the problems, BDDRPA* still works more efficiently.
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AI 2006: Advances in Artificial Intelligence
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© 2006 Springer : Reproduced in accordance with the copyright policy of the publisher : The original publication will be available at SpringerLink (use hypertext links)