Genetic Systems Programming

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Details

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.


Inhalt
Evolutionary Computation: from Genetic Algorithms to Genetic Programming.- Automatically Defined Functions in Gene Expression Programming.- Evolving Intrusion Detection Systems.- Evolutionary Pattern Matching Using Genetic Programming.- Genetic Programming in Data Modelling.- Stock Market Modeling Using Genetic Programming Ensembles.- Evolutionary Digital Circuit Design Using Genetic Programming.- Evolving Complex Robotic Behaviors Using Genetic Programming.- Automatic Synthesis of Microcontroller Assembly Code Through Linear Genetic Programming.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783540298496
    • Editor Nadia Nedjah
    • Sprache Englisch
    • Auflage 2006. 2006
    • Größe H24mm x B234mm x T164mm
    • Jahr 2006
    • EAN 9783540298496
    • Format Fester Einband
    • ISBN 978-3-540-29849-6
    • Titel Genetic Systems Programming
    • Untertitel Theory and Experiences
    • Gewicht 706g
    • Herausgeber Springer-Verlag GmbH
    • Anzahl Seiten 234
    • Lesemotiv Verstehen
    • Genre Informatik

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