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.
Supported by the Australian Research Council grant DP0452628, National Basic Research 973 Program of China under grant 2005CB321902, National Natural Science Foundation of China grants 60496327, 10410638 and 60473004,and Guangdong Provincial Natural Science Foundation grants 04205407 and 06023195.
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Yue, W., Xu, Y., Su, K. (2006). BDDRPA*: An Efficient BDD-Based Incremental Heuristic Search Algorithm for Replanning. In: Sattar, A., Kang, Bh. (eds) AI 2006: Advances in Artificial Intelligence. AI 2006. Lecture Notes in Computer Science(), vol 4304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941439_67
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DOI: https://doi.org/10.1007/11941439_67
Publisher Name: Springer, Berlin, Heidelberg
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