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Heavy-Tailed Distributions in Combinatorial Search (1997)
| Citations: | 75 - 14 self |
BibTeX
@MISC{Gomes97heavy-taileddistributions,
author = {Carla Gomes and Bart Selman and Nuno Crato},
title = {Heavy-Tailed Distributions in Combinatorial Search},
year = {1997}
}
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Abstract
Combinatorial search methods often exhibit a large variability in performance. We study the cost profiles of combinatorial search procedures. Our study reveals some intriguing properties of such cost profiles. The distributions are often characterized by very long tails or "heavy tails". We will show that these distributions are best characterized by a general class of distributions that have no moments (i.e., an infinite mean, variance, etc.). Such non-standard distributions have recently been observed in areas as diverse as economics, statistical physics, and geophysics. They are closely related to fractal phenomena, whose study was introduced by Mandelbrot. We believe this is the first finding of these distributions in a purely computational setting. We also show how random restarts can effectively eliminate heavy-tailed behavior, thereby dramatically improving the overall performance of a search procedure.
Keyphrases
combinatorial search heavy-tailed distribution cost profile purely computational setting heavy tail statistical physic infinite mean combinatorial search procedure random restarts large variability search procedure non-standard distribution overall performance fractal phenomenon intriguing property combinatorial search method heavy-tailed behavior first finding general class
