Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.
Author(s): Colin R. Reeves Jonathan E. Rowe
Edition: 1
Year: 2002
Language: English
Pages: 344
Preliminaries......Page 1
Contents......Page 6
1 Introduction......Page 14
2 Basic Principles......Page 32
3 Schema Theory......Page 78
4 No Free Lunch for GAs......Page 108
5 GAs as Markov Processes......Page 124
6 The Dynamical Systems Model......Page 154
7 Statistical Mechanics Approximations......Page 186
8 Predicting GA Performance......Page 214
9 Landscapes......Page 244
10 Summary......Page 278
A Test Problems......Page 300
Bibliography......Page 308
Index......Page 340
