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Analyzing Evolutionary Algorithms : The Computer Science Perspective / by Thomas Jansen.
- Format:
- Book
- Author/Creator:
- Jansen, Thomas, author.
- Series:
- Computer Science (Springer-11645)
- Natural computing series 1619-7127
- Natural Computing Series, 1619-7127
- Language:
- English
- Subjects (All):
- Computers.
- Computational intelligence.
- Mathematical optimization.
- Artificial intelligence.
- Theory of Computation.
- Computational Intelligence.
- Optimization.
- Artificial Intelligence.
- Local Subjects:
- Theory of Computation.
- Computational Intelligence.
- Optimization.
- Artificial Intelligence.
- Physical Description:
- 1 online resource (X, 258 pages).
- Edition:
- First edition 2013.
- Contained In:
- Springer eBooks
- Place of Publication:
- Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
- System Details:
- text file PDF
- Summary:
- Evolutionary algorithms is a class of randomized heuristics inspired by natural evolution. They are applied in many different contexts, in particular in optimization, and analysis of such algorithms has seen tremendous advances in recent years. In this book the author provides an introduction to the methods used to analyze evolutionary algorithms and other randomized search heuristics. He starts with an algorithmic and modular perspective and gives guidelines for the design of evolutionary algorithms. He then places the approach in the broader research context with a chapter on theoretical perspectives. By adopting a complexity-theoretical perspective, he derives general limitations for black-box optimization, yielding lower bounds on the performance of evolutionary algorithms, and then develops general methods for deriving upper and lower bounds step by step. This main part is followed by a chapter covering practical applications of these methods. The notational and mathematical basics are covered in an appendix, the results presented are derived in detail, and each chapter ends with detailed comments and pointers to further reading. So the book is a useful reference for both graduate students and researchers engaged with the theoretical analysis of such algorithms. .
- Contents:
- Introduction
- Evolutionary Algorithms and Other Randomized Search Heuristics
- Theoretical Perspectives on Evolutionay Algorithms
- General Limits in Black-Box Optimization
- Methods for the Analysis of Evolutionary Algorithms
- Selected Topics in the Analysis of Evolutionary Algorithms
- App. A, Landau Notation
- App. B, Tail Estimations
- App. C, Martingales and Applications.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-642-17339-4
- 9783642173394
- Access Restriction:
- Restricted for use by site license.
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