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Other titles in the Natural Computing series:

Analyzing Evolutionary Algorithms: The Computer Science Perspective (Natural Computing)

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Analyzing Evolutionary Algorithms: The Computer Science Perspective (Natural Computing) Cover

 

Synopses & Reviews

Publisher Comments:

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.

About the Author

The author lectured and researched in the Technische Universität Dortmund for 9 years after his PhD, and he is now the Stokes College Lecturer in the Department of Computer Science in University College Cork. He has tested the book content in his own lectures at these universities, and he has been invited to run the tutorial on this subject at the main international conference on evolutionary computing, GECCO.

Table of 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.

Product Details

ISBN:
9783642173387
Author:
Jansen, Thomas
Publisher:
Springer
Subject:
Personal Computers-General
Subject:
Computer Science
Subject:
Black-Box Optimization
Subject:
Complexity-Theoretical Analysis
Subject:
Evoluionary Computing (EC)
Subject:
Evolutionary Algorithms (EAs)
Subject:
Natural Computing
Subject:
Randomized Search Heuristics
Subject:
Theory of computation
Subject:
Computational intelligence
Subject:
OPTIMIZATION
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Opt
Subject:
imization
Copyright:
Edition Description:
2011
Series:
Natural Computing Series
Publication Date:
20121231
Binding:
HARDCOVER
Language:
English
Pages:
265
Dimensions:
235 x 155 mm

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Computers and Internet » Networking » General
Computers and Internet » Personal Computers » General
Computers and Internet » Software Engineering » Algorithms
Engineering » Construction » General
Science and Mathematics » Mathematics » Computer

Analyzing Evolutionary Algorithms: The Computer Science Perspective (Natural Computing) New Hardcover
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