Foundations of genetic algorithms 6 / edited by Worthy N. Martin and William M. Spears.

Format:

Book

Conference/Event

Contributor:

Martin, W. N. (Worthy N.)

Spears, William M., 1962-

Conference Name:

Workshop on Foundations of Genetic Algorithms (6th : 2000 : Charlottesville, Va.)

Series:

Morgan Kaufmann series in evolutionary computation.

The Morgan Kaufmann series in evolutionary computation, 1081-6593

Language:

English

Subjects (All):

Genetic algorithms--Congresses.

Genetic algorithms.

Mathematical optimization.

Physical Description:

1 online resource (351 p.)

Edition:

First edition.

Other Title:

Foundations of genetic algorithms six

Place of Publication:

San Francisco : Morgan Kaufmann, c2001.

Language Note:

English

System Details:

text file

Summary:

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

Contents:

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

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.

ISBN:

9786611072896

9781281072894

1281072893

9780080506876

0080506879

OCLC:

476112750