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Table of contents (9 chapters)
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Front Matter
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Back Matter
About this book
Designing complex programs such as operating systems, compilers, filing systems, data base systems, etc. is an old ever lasting research area. Genetic programming is a relatively new promising and growing research area. Among other uses, it provides efficient tools to deal with hard problems by evolving creative and competitive solutions. Systems Programming is generally strewn with such hard problems. This book is devoted to reporting innovative and significant progress about the contribution of genetic programming in systems programming. The contributions of this book clearly demonstrate that genetic programming is very effective in solving hard and yet-open problems in systems programming. Followed by an introductory chapter, in the remaining contributed chapters, the reader can easily learn about systems where genetic programming can be applied successfully. These include but are not limited to, information security systems, compilers, data mining systems, stock market prediction systems, robots and automatic programming.
Editors and Affiliations
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Faculdade de Engenharia, Universidade do Estado do Rio de Janeiro, MaracanĂ£, Rio de Janeiro, Brazil
Nadia Nedjah, Luiza de Macedo Mourelle
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School for Computer Science and, Engineering, Chung-Ang University, Seoul, Korea Republic of (South Korea)
Ajith Abraham
Bibliographic Information
Book Title: Genetic Systems Programming
Book Subtitle: Theory and Experiences
Editors: Nadia Nedjah, Luiza de Macedo Mourelle, Ajith Abraham
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/3-540-32498-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2006
Hardcover ISBN: 978-3-540-29849-6Published: 12 January 2006
Softcover ISBN: 978-3-642-06753-2Published: 12 February 2010
eBook ISBN: 978-3-540-32498-0Published: 21 July 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XXII, 234
Number of Illustrations: 114 b/w illustrations
Topics: Mathematical and Computational Engineering, Artificial Intelligence