DocumentCode
843434
Title
Guest Editors´ Introduction: Monte Carlo Methods
Author
Beichl, Isabel ; Sullivan, Francis
Author_Institution
National Institute of Standards and Technology
Volume
8
Issue
2
fYear
2006
Firstpage
7
Lastpage
8
Abstract
The term Monte Carlo method stands for any member of a very large class of computational methods that use randomness to generate "typical" instances of a problem under investigation. Typical instances are generated because it\´s impractical or even impossible to generate all instances. A set of typical instances is supposed to help us learn something about a problem of interest. Most of the time, Monte Carlo works amazingly well, but when used blindly, with no firm basis in theory, it can yield some very strange results or run for many, many hours and yield nothing. One of the triumphs of the modern period in Monte Carlo methods has been a dramatic improvement in our understanding of how to speed up the computation and how to know when the method will work.
Keywords
Markov chains; Monte Carlo; algorithm; randomness; Acceleration; Convergence; Game theory; Kinetic theory; Monte Carlo methods; NIST; Needles; Probability distribution; Terminology; Markov chains; Monte Carlo; algorithm; randomness;
fLanguage
English
Journal_Title
Computing in Science & Engineering
Publisher
ieee
ISSN
1521-9615
Type
jour
DOI
10.1109/MCSE.2006.27
Filename
1599368
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