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Author(s):  
Shuli Hu ◽  
Nathan R. Sturtevant

While computing resources have continued to grow, methods for building and using large heuristics have not seen significant advances in recent years. We have observed that direction-optimizing breadth-first search, developed for and used broadly in the Graph 500 competition, can also be applied for building heuristics. But, the algorithm cannot run efficiently using external memory -- when the heuristics being built are larger than RAM. This paper shows how to modify direction-optimizing breadth-first search to build external-memory heuristics. We show that the new approach is not effective in state spaces with low asymptotic branching factors, but in other domains we are able to achieve up to a 3x reducing in runtime when building an external-memory heuristic. The approach is then used to build a 2.6TiB Rubik's Cube heuristic with 5.8 trillion entries, the largest pattern database heuristic ever built.


2016 ◽  
Author(s):  
Max Grossman ◽  
Howard Porter Pritchard Jr. ◽  
Zoran Budimlic ◽  
Vivek Sarkar
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2013 ◽  
Vol 57 (1/2) ◽  
pp. 10:1-10:11 ◽  
Author(s):  
F. Checconi ◽  
F. Petrini

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