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Foundations of genetic algorithms 6 [electronic resource]

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Foundations of Genetic Algorithms, Volume 6 is the latest in a series of books that records the prestigious Foundations of Genetic Algorithms Workshops, sponsored and organised by the International Society of Genetic Algorithms specifically to address theoretical publications on genetic algorithms and classifier systems.Genetic algorithms are one of the more successful machine learning methods. Based on the metaphor of natural evolution, a genetic algorithm searches the available information in any given task and seeks the optimum solution by replacing weaker populations with stronger

Title Foundations of genetic algorithms 6 [electronic resource] / edited by Worthy N. Martin and William M. Spears.
Edition First edition.
Publisher San Francisco : Morgan Kaufmann
Creation Date c2001
Notes "The 2000 Foundations of Genetic Algorithms (FOGA-6) workshop was the sixth biennial meeting in this series of workshops"--P. 1.
Includes bibliographical references and indexes.
English
Content Front Cover
Foundations of Genetic Algorithms6
Copyright Page
Contents
Chapter 1. Introduction
Chapter 2. Overcoming Fitness Barriers in Multi-Modal Search Spaces
Chapter 3. Niches in NK-Landscapes
Chapter 4. New Methods for Tunable, Random Landscapes
Chapter 5. Analysis of Recombinative Algorithms on a Non-Separable Building-Block Problem
Chapter 6. Direct Statistical Estimation of GA Landscape Properties
Chapter 7. Comparing Population Mean Curves
Chapter 8. Local Performance of the ((/(I, () -ES in a Noisy Environment
Chapter 9. Recursive Conditional Scheme Theorem, Convergence and Population Sizing in Genetic AlgorithmsChapter 10. Towards a Theory of Strong Overgeneral Classifiers
Chapter 11. Evolutionary Optimization through PAC Learning
Chapter 12. Continuous Dynamical System Models of Steady-State Genetic Algorithms
Chapter 13. Mutation-Selection Algorithm: A Large Deviation Approach
Chapter 14. The Equilibrium and Transient Behavior of Mutation and Recombination
Chapter 15. The Mixing Rate of Different Crossover Operators
Chapter 16. Dynamic Parameter Control in Simple Evolutionary Algorithms
Chapter 17. Local Search and High Precision Gray Codes: Convergence Results and NeighborhoodsChapter 18. Burden and Benefits of Redundancy
Author Index
Key Word Index
Series The Morgan Kaufmann series in evolutionary computation, 1081-6593
Extent 1 online resource (351 p.)
Language English
National Library system number 997010710624205171
MARC RECORDS
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