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

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

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.

Keywords

  • Algorithm Selection Problem
  • Graph Search
  • Grammar Problem
  • Distributional Goals
  • Hutter 2015b

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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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.

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Correspondence to Tom Everitt .

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© 2015 Springer International Publishing Switzerland

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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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