Noisy Optimization With Evolution Strategies: Genetic Algorithms and Evolutionary Computation, cartea 8
Autor Dirk V. Arnolden Limba Engleză Paperback – 24 oct 2012
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.
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Specificații
ISBN-13: 9781461353973
ISBN-10: 1461353971
Pagini: 172
Ilustrații: IX, 158 p.
Dimensiuni: 155 x 235 x 9 mm
Greutate: 0.25 kg
Ediția:Softcover reprint of the original 1st ed. 2002
Editura: Springer Us
Colecția Springer
Seria Genetic Algorithms and Evolutionary Computation
Locul publicării:New York, NY, United States
ISBN-10: 1461353971
Pagini: 172
Ilustrații: IX, 158 p.
Dimensiuni: 155 x 235 x 9 mm
Greutate: 0.25 kg
Ediția:Softcover reprint of the original 1st ed. 2002
Editura: Springer Us
Colecția Springer
Seria Genetic Algorithms and Evolutionary Computation
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
1. Introduction.- 2. Preliminaries.- 1 The Basic $$({\mu \mathord{\left/{\vphantom {\mu {\rho \mathop + \limits_, \lambda }}} \right.\kern-\nulldelimiterspace} {\rho \mathop + \limits_, \lambda }}) - ES$$.- 2 Mutation Strength Adaptation.- 3 Fitness Environments.- 4 Measuring Performance.- 5 Modeling the Sphere.- 3. The (1 + 1)-ES: Overvaluation.- 1 Overvaluation.- 2 Performance.- 3 Discussion.- 4. The (?,?)-ES: Distributed Populations.- 1 Modeling the Population.- 2 The Infinite Noise Limit.- 3 Finite Noise Strength.- 4 The Spherical Environment.- 5. The (?/?,?)-ES: Genetic Repair.- 1 Simple Performance Analysis.- 2 Improving the Accuracy.- 3 Cumulative Mutation Strength Adaptation.- 6. Comparing Approaches To Noisy Optimization.- 1 The Competitors.- 2 The Competition.- 7. Conclusions.- Appendices.- References.
Recenzii
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)
"[...]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)