Editors:
- one of the hottest topics in evolutionary computation
- excellent compilation of carefully selected topics in estimation of distribution algorithms---search algorithms that combine ideas from evolutionary algorithms and machine learning.
- an eye-opener and a must-read text, covering easy-to-read yet erudite articles on established and emerging EDA methodologies from real experts in the field.
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 33)
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Table of contents (15 chapters)
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Front Matter
About this book
Editors and Affiliations
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Department of Math. And Computer Science, University of Missouri at St. Louis, One University Blvd., St. Louis, USA
Martin Pelikan
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Department of Industrial and Enterprise Systems Engineering, Illinois Genetic Algorithms Laboratory, 414 TB, Urbana, USA
Kumara Sastry
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Yahoo! Inc., Sunnyvale, USA
Erick CantúPaz
Bibliographic Information
Book Title: Scalable Optimization via Probabilistic Modeling
Book Subtitle: From Algorithms to Applications
Editors: Martin Pelikan, Kumara Sastry, Erick CantúPaz
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-34954-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2006
Hardcover ISBN: 978-3-540-34953-2Published: 25 September 2006
Softcover ISBN: 978-3-642-07116-4Published: 30 November 2010
eBook ISBN: 978-3-540-34954-9Published: 12 January 2007
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XX, 349
Topics: Probability Theory and Stochastic Processes, Mathematical and Computational Engineering, Artificial Intelligence