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Analytical Results on the BFS vs. DFS Algorithm Selection Problem: Part II: Graph Search

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AI 2015: Advances in Artificial Intelligence (AI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9457))

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Abstract

The algorithm selection problem asks to select the best algorithm for a given problem. In the companion paper (Everitt and Hutter 2015b), expected runtime was approximated as a function of search depth and probabilistic goal distribution for tree search versions of breadth-first search (BFS) and depth-first search (DFS). Here we provide an analogous analysis of BFS and DFS graph search, deriving expected runtime as a function of graph structure and goal distribution. The applicability of the method is demonstrated through analysis of two different grammar problems. The approximations come surprisingly close to empirical reality.

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Notes

  1. 1.

    Source code for the experiments is available at http://tomeveritt.se.

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Acknowledgements

Thanks to David Johnston for proof reading final drafts of both papers.

Author information

Authors and Affiliations

  1. Australian National University, Canberra, Australia

    Tom Everitt & Marcus Hutter

Authors
  1. Tom Everitt
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  2. Marcus Hutter
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Corresponding author

Correspondence to Tom Everitt .

Editor information

Editors and Affiliations

  1. The University of Waikato, Hamilton, New Zealand

    Bernhard Pfahringer

  2. The Australian National University, Canberra, Aust Capital Terr, Australia

    Jochen Renz

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Everitt, T., Hutter, M. (2015). Analytical Results on the BFS vs. DFS Algorithm Selection Problem: Part II: Graph Search. In: Pfahringer, B., Renz, J. (eds) AI 2015: Advances in Artificial Intelligence. AI 2015. Lecture Notes in Computer Science(), vol 9457. Springer, Cham. https://doi.org/10.1007/978-3-319-26350-2_15

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  • DOI: https://doi.org/10.1007/978-3-319-26350-2_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26349-6

  • Online ISBN: 978-3-319-26350-2

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