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Evolutionary Computation for Modeling and Optimization

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  • 572 Seiten
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Evolutionary Computation for Optimization and Modeling is an introduction to evolutionary computation, a field which includes gene... Weiterlesen
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Evolutionary Computation for Optimization and Modeling is an introduction to evolutionary computation, a field which includes genetic algorithms, evolutionary programming, evolution strategies, and genetic programming. The text is a survey of some application of evolutionary algorithms. It introduces mutation, crossover, design issues of selection and replacement methods, the issue of populations size, and the question of design of the fitness function. It also includes a methodological material on efficient implementation. Some of the other topics in this book include the design of simple evolutionary algorithms, applications to several types of optimization, evolutionary robotics, simple evolutionary neural computation, and several types of automatic programming including genetic programming. The book gives applications to biology and bioinformatics and introduces a number of tools that can be used in biological modeling, including evolutionary game theory. Advanced techniques such as cellular encoding, grammar based encoding, and graph based evolutionary algorithms are also covered. This book presents a large number of homework problems, projects, and experiments, with a goal of illustrating single aspects of evolutionary computation and comparing different methods. Its readership is intended for an undergraduate or first-year graduate course in evolutionary computation for computer science, engineering, or other computational science students. Engineering, computer science, and applied math students will find this book a useful guide to using evolutionary algorithms as a problem solving tool.


Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.


An Overview of Evolutionary Computation.- Designing Simple Evolutionary Algorithms.- Optimizing Real Values Functions.- Sunburn: Co-evolving Strings.- Small Neural Nets: Symbots.- Evolving Finite State Automata.- Ordered Structures.- Plus One Recall Store.- Fitting to Data.- Tartarus: Discrete Robotics.- Evolving Logic Gates.- ISAc lists: Alternative Genetic Programming.- Graph Based Evolutionary Algorithms.- Cellular Encoding.- Application to Bioinformatics.- Glossary.- Appendices.- References.- Index.


Titel: Evolutionary Computation for Modeling and Optimization
EAN: 9780387319094
ISBN: 978-0-387-31909-4
Digitaler Kopierschutz: Adobe-DRM
Format: E-Book (pdf)
Herausgeber: Springer, New York
Genre: Naturwissenschaft
Anzahl Seiten: 572
Veröffentlichung: 04.04.2006
Jahr: 2006
Untertitel: Englisch
Dateigrösse: 3.2 MB