Foreword. Acknowledgments. 1. Introduction. 2. Preliminaries. 3. The (1+1)-ES: Overvaluation. 4. The (mu, lambda)-ES: Distributed Populations. 5. The (mu/mu, lambda-ES: Genetic Repair. 6. Comparing Approaches to Noisy Optimization. 7. Conclusions. Appendices. A. Some Statistical Basics. B. Some Useful Identities. C. Computing the Overvaluation. D. Determining the Effects of Sampling and Selection. References. Index.
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