Analytical Results on the BFS vs. DFS Algorithm Selection Problem: Part II: Graph Search
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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.
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.
Notes
Acknowledgements
Thanks to David Johnston for proof reading final drafts of both papers.
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