Noisy Optimization With Evolution Strategies
Language: English
Published by Springer US, Springer New York Okt 2012, 2012
- Softcover
- New

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This item is printed on demand - Print on Demand Titel. Neuware -Noise is a common factor in most real-world optimization problems. Sources of noise can include physical measurement limitations, stochastic simulation models, incomplete sampling of large spaces, and human-computer interaction. Evolutionary algorithms are general, nature-inspired heuristics for numerical search and optimization that are frequently observed to be particularly robust with regard to the effects of noise.Noisy Optimization with Evolution Strategies contributes to the understanding of evolutionary optimization in the presence of noise by investigating the performance of evolution strategies, a type of evolutionary algorithm frequently employed for solving real-valued optimization problems. By considering simple noisy environments, results are obtained that describe how the performance of the strategies scales with both parameters of the problem and of the strategies considered. Such scaling laws allow for comparisons of different strategy variants, for tuning evolution strategies for maximum performance, and they offer insights and an understanding of the behavior of the strategies that go beyond what can be learned from mere experimentation.This first comprehensive work on noisy optimization with evolution strategies investigates the effects of systematic fitness overvaluation, the benefits of distributed populations, and the potential of genetic repair for optimization in the presence of noise. The relative robustness of evolution strategies is confirmed in a comparison with other direct search algorithms.Noisy Optimization with Evolution Strategies is an invaluable resource for researchers and practitioners of evolutionary algorithms.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch.…
Seller Inventory # 9781461353973
- Title
- Noisy Optimization With Evolution Strategies
- Author
- Dirk V. Arnold
- Publisher
- Springer US, Springer New York Okt 2012
- Publication year
- 2012
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1461353971
- ISBN 13
- 9781461353973
- Item weight
- 271 grams
- Dimensions
- 235x155x10 mm
Noise is a common factor in most real-world optimization problems. Sources of noise can include physical measurement limitations, stochastic simulation models, incomplete sampling of large spaces, and human-computer interaction. Evolutionary algorithms are general, nature-inspired heuristics for numerical search and optimization that are frequently observed to be particularly robust with regard to the effects of noise.
Noisy Optimization with Evolution Strategies contributes to the understanding of evolutionary optimization in the presence of noise by investigating the performance of evolution strategies, a type of evolutionary algorithm frequently employed for solving real-valued optimization problems. By considering simple noisy environments, results are obtained that describe how the performance of the strategies scales with both parameters of the problem and of the strategies considered. Such scaling laws allow for comparisons of different strategy variants, for tuning evolution strategies for maximum performance, and they offer insights and an understanding of the behavior of the strategies that go beyond what can be learned from mere experimentation.
This first comprehensive work on noisy optimization with evolution strategies investigates the effects of systematic fitness overvaluation, the benefits of distributed populations, and the potential of genetic repair for optimization in the presence of noise. The relative robustness of evolution strategies is confirmed in a comparison with other direct search algorithms.
Noisy Optimization with Evolution Strategies is an invaluable resource for researchers and practitioners of evolutionary algorithms.
"Synopsis" may belong to another edition of this title.
Review
From the reviews:
"[...]a highly interesting book recommendable to anyone interested in evolutionary optimization and to those facing noisy optimization problems."
(Hans-Georg Beyer)
"The book addresses one of the most pressing and interesting topics in evolutionary computation research – the performance of evolutional algorithms in uncertain environments ... . Summing up, the book appears to be an interesting theoretical complement to many existing books describing practical applications of evolutionary computations." (Jacek Blazewicz, Zentralblatt MATH, Vol. 1103 (5), 2007)
"About the title" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
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