Overview
- Everything about evolutionary computation in practice
Part of the book series: Studies in Computational Intelligence (SCI, volume 88)
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Table of contents (15 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book is loaded with examples in which computer scientists and engineers have used evolutionary computation—programs that mimic natural evolution—to solve real problems. They aren’t abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions. Some of the authors have already won "Humies"—Human Competitive Results Awards—for the work described in this book. I highly recommend it as a highly concentrated source of good problem-solving approaches that are applicable to many real-world problems.
--Erik Goodman, Vice President, Red Cedar Technology, Inc.; Professor, Electrical & Computer Engineering, Michigan State University; and Founding Chair, ACM SIGEVO, the Special Interest Group on Genetic and Evolutionary Computation of the Association for Computing Machinery
Reviews
From the reviews:
"‘Evolutionary Computation in Practice’ … focuses on real-world challenges and on technology transfer from academia to industry. It is of interest to everyone working on machine learning. … is well-written, easy to read and provides a comprehensive coverage of the field. … This enables the appropriate and successful use of EC. It inspires academic researchers by demonstrating the value of their work, and guides them in their development of EC. It is an excellent contribution to the Studies in Computational Intelligence series." (Larry M. Deschaine, Genetic Programming and Evolvable Machines, Vol. 9, March, 2008)
Editors and Affiliations
Bibliographic Information
Book Title: Evolutionary Computation in Practice
Editors: Tina Yu, Lawrence Davis, Cem Baydar, Rajkumar Roy
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-75771-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-75770-2Published: 04 January 2008
Softcover ISBN: 978-3-642-09492-7Published: 30 November 2010
eBook ISBN: 978-3-540-75771-9Published: 23 January 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIV, 322
Topics: Mathematical and Computational Engineering, Artificial Intelligence