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Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part I: Tree 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

Breadth-first search (BFS) and depth-first search (DFS) are the two most fundamental search algorithms. We derive approximations of their expected runtimes in complete trees, as a function of tree depth and probabilistic goal distribution. We also demonstrate that the analytical approximations are close to the empirical averages for most parameter settings, and that the results can be used to predict the best algorithm given the relevant problem features.

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Notes

  1. 1.

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

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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 I: Tree 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_14

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  • DOI: https://doi.org/10.1007/978-3-319-26350-2_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26349-6

  • Online ISBN: 978-3-319-26350-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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