BDDRPA*: an efficient BDD-Based incremental heuristic search algorithm for replanning

Authors:
Weiya Yue;Yanyan Xu;Kaile Su
Affiliations:
Department of Computer Science, Sun Yat-sen University, Guangzhou, China;Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China;Department of Computer Science, Sun Yat-sen University, Guangzhou, China
Venue:
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Year:
2006

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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.