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Genetic Algorithms: Principles and Perspectives : A Guide to GA Theory
1. Introduction. 2. Basic Principles. 3. Schema Theory. 4. Non Free Lunch for GAs. 5. GAs as Markov Processes. 6. The Dynamical Systems Model. 7. Statistical Mechanics Approximations. 8. Predicting GA Performance. 9. Landschapes. 10. Summary. Test Problems. Bibliography. Index.
348 pages, Paperback
First published December 31, 2002
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