Treffer: Formal models of heavy-tailed behavior in combinatorial search

Title:
Formal models of heavy-tailed behavior in combinatorial search
Source:
CP 2001 : principles and practice of constraint programming (Paphos, 26 November - 1 December 2001)Lecture notes in computer science. :408-421
Publisher Information:
Berlin: Springer, 2001.
Publication Year:
2001
Physical Description:
print, 13 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science, Cornell University, Ithaca, NY 14853, United States
ISSN:
0302-9743
Rights:
Copyright 2002 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Operational research. Management
Accession Number:
edscal.14046045
Database:
PASCAL Archive

Weitere Informationen

Recently, it has been found that the cost distributions of randomized backtrack search in combinatorial domains are often heavy-tailed. Such heavy-tailed distributions explain the high variability observed when using backtrack-style procedures. A good understanding of this phenomenon can lead to better search techniques. For example, restart strategies provide a good mechanism for eliminating the heavy-tailed behavior and boosting the overall search performance. Several state-of-the-art SAT solvers now incorporate such restart mechanisms. The study of heavy-tailed phenomena in combinatorial search has so far been been largely based on empirical data. We introduce several abstract tree search models, and show formally how heavy-tailed cost distribution can arise in backtrack search. We also discuss how these insights may facilitate the development of better combinatorial search methods.