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AAAI 2006

A Breadth-First Approach to Memory-Efficient Graph Search

Conference Paper New Scientific and Technical Advances in Research (Nectar) Papers Artificial Intelligence

Abstract

Recent work shows that the memory requirements of A* and related graph-search algorithms can be reduced substantially by only storing nodes that are on or near the search frontier, using special techniques to prevent node regeneration, and recovering the solution path by a divide-and-conquer technique. When this approach is used to solve graph-search problems with unit edge costs, we have shown that a breadth-first search strategy can be more memory-efficient than a best-first strategy. We provide an overview of our work using this approach, which we call breadth-first heuristic search.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
1133463728686254393
v2026.09.13