Theoretical Aspects of Evolutionary Computing

By: Leila Kallel (Editor), Bart Naudts (Editor), Alex Rogers (Editor)

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Hardcover | 8 May 2001

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514 Pages

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23.5 x 15.88 x 3.18

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During the first week of September 1999, the Second EvoNet Summer School on Theoretical Aspects of Evolutionary Computing was held at the Middelheim cam pus of the University of Antwerp, Belgium. Originally intended as a small get together of PhD students interested in the theory of evolutionary computing, the summer school grew to become a successful combination of a four-day workshop with over twenty researchers in the field and a two-day lecture series open to a wider audience. This book is based on the lectures and workshop contributions of this summer school. Its first part consists of tutorial papers which introduce the reader to a num ber of important directions in the theory of evolutionary computing. The tutorials are at graduate level andassume only a basic backgroundin mathematics and com puter science. No prior knowledge ofevolutionary computing or its theory is nec essary. The second part of the book consists of technical papers, selected from the workshop contributions. A number of them build on the material of the tutorials, exploring the theory to research level. Other technical papers may require a visit to the library.

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Introduction to Evolutionary Computing in Design Search and Optimisation	p. 1
Evolutionary Algorithms and Constraint Satisfaction: Definitions, Survey, Methodology, and Research Directions	p. 13
The Dynamical Systems Model of the Simple Genetic Algorithm	p. 31
Modelling Genetic Algorithm Dynamics	p. 59
Statistical Mechanics Theory of Genetic Algorithms	p. 87
Theory of Evolution Strategies - A Tutorial	p. 109
Evolutionary Algorithms: From Recombination to Search Distributions	p. 135
Properties of Fitness Functions and Search Landscapes	p. 175
A Solvable Model of a Hard Optimisation Problem	p. 207
Bimodal Performance Profile of Evolutionary Search and the Effects of Crossover	p. 223
Evolution Strategies in Noisy Environments - A Survey of Existing Work	p. 239
Cyclic Attractors and Quasispecies Adaptability	p. 251
Genetic Algorithms in Time-Dependent Environments	p. 261
Statistical Machine Learning and Combinatorial Optimization	p. 287
Multi-Parent Scanning Crossover and Genetic Drift	p. 307
Harmonic Recombination for Evolutionary Computation	p. 331
How to Detect all Maxima of a Function	p. 343
On Classification of Fitness Functions	p. 371
Genetic Search on Highly Symmetric Solution Spaces: Preliminary Results	p. 387
Structure Optimization and Isomorphisms	p. 409
Detecting Spin-Flip Symmetry in Optimization Problems	p. 423
Asymptotic Results for Genetic Algorithms with Applications to Nonlinear Estimation	p. 439
Index	p. 495
Table of Contents provided by Blackwell. All Rights Reserved.

Theoretical Aspects of Evolutionary Computing

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