ML Anthology

Comparing Search Algorithms Using Sorting and Hashing on Disk and in Memory

Richard E. Korf
IJCAI 2016 pp. 610-616
/ijcai/2016/korf2016ijcai-comparing/

Abstract

We compare sorting and hashing for implicit graph search using disk storage. We first describe efficient pipelined implementations of both algorithms, which reduce disk I/O. We then compare the two algorithms and find that hashing is faster, but that sorting requires less disk storage. We also compare disk-based with in-memory search, and surprisingly find that there is little or no time overhead associated with disk-based search. We present experimental results on the sliding-tile puzzles, Rubik's Cube, and the 4-peg Towers of Hanoi. PDF

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Cite

Text

Korf. "Comparing Search Algorithms Using Sorting and Hashing on Disk and in Memory." International Joint Conference on Artificial Intelligence, 2016.

Markdown

[Korf. "Comparing Search Algorithms Using Sorting and Hashing on Disk and in Memory." International Joint Conference on Artificial Intelligence, 2016.](https://mlanthology.org/ijcai/2016/korf2016ijcai-comparing/)

BibTeX

@inproceedings{korf2016ijcai-comparing,
  title     = {{Comparing Search Algorithms Using Sorting and Hashing on Disk and in Memory}},
  author    = {Korf, Richard E.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {610-616},
  url       = {https://mlanthology.org/ijcai/2016/korf2016ijcai-comparing/}
}