| 書目名稱 | Noisy Optimization With Evolution Strategies | | 編輯 | Dirk V. Arnold | | 視頻video | http://file.papertrans.cn/667/666803/666803.mp4 | | 叢書名稱 | Genetic Algorithms and Evolutionary Computation | | 圖書封面 |  | | 描述 | .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 comprehens | | 出版日期 | Book 2002 | | 關(guān)鍵詞 | algorithms; behavior; evolution; evolutionary algorithm; heuristics; human-computer interaction (HCI); opt | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4615-1105-2 | | isbn_softcover | 978-1-4613-5397-3 | | isbn_ebook | 978-1-4615-1105-2Series ISSN 1568-2587 | | issn_series | 1568-2587 | | copyright | Springer Science+Business Media New York 2002 |
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