Depth-first vs best-first search

Authors:
Nageshwara Rao Vempaty;Vipin Kumar;Richard E. Korf
Affiliations:
Dept. of Computer Sciences, Univ. of Central Florida, Orlando, FL;Computer Science Dept., Univ. of Minnesota, Minneapolis, MN;Dept. of Computer Science, Univ. of California, Los Angeles, CA
Venue:
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 1
Year:
1991

Citing 5
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Abstract

We present a comparison of three well known heuristic search algorithms: best-first search (BFS), iterative-deepening (ID), and depth-first branch-and-bound (DFBB). We develop a model to analyze the time and space complexity of these three algorithms in terms of the heuristic branching factor and solution density. Our analysis identifies the types of problems on which each of the search algorithms performs better than the other two. These analytical results are validated through experiments on different problems. We also present a new algorithm, DFS*, which is a hybrid of iterative deepening and depth-first branch-and-bound, and show that it outperforms the other three algorithms on some problems.