Simulated Evolution and Learning, Xin Yao; Jong-Hwan Kim; Takeshi Furuhashi

Автор: Tzai-Der Wang; Xiaodong Li; Xufa Wang
Название: Simulated Evolution and Learning
ISBN: 3540473319 ISBN-13(EAN): 9783540473312
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This book constitutes the refereed proceedings of the 6th International Conference on Simulated Evolution and Learning, SEAL 2006, held in Hefei, China in October 2006. The 117 revised full papers presented were carefully reviewed and selected from 420 submissions.

Автор: Xiaodong Li; Michael Kirley; Mengjie Zhang; Vic Ci
Название: Simulated Evolution and Learning
ISBN: 3540896937 ISBN-13(EAN): 9783540896937
Издательство: Springer
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Цена: 16070.00 р.
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Описание: Constitutes the proceedings of the 7th International Conference on Simulated Evolution and Learning, SEAL 2008, held in Melbourne, Australia, during December 7-10, 2008. This volume covers topics such as evolutionary learning; evolutionary optimisation; hybrid learning; adaptive systems; and theoretical issues in evolutionary computation.

Автор: Kramer
Название: Machine Learning for Evolution Strategies
ISBN: 331933381X ISBN-13(EAN): 9783319333816
Издательство: Springer
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Цена: 16979.00 р.
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Описание: This bookintroduces numerous algorithmic hybridizations between both worlds that showhow machine learning can improve and support evolution strategies. The set ofmethods comprises covariance matrix estimation, meta-modeling of fitness andconstraint functions, dimensionality reduction for search and visualization ofhigh-dimensional optimization processes, and clustering-based niching. Aftergiving an introduction to evolution strategies and machine learning, the bookbuilds the bridge between both worlds with an algorithmic and experimentalperspective. Experiments mostly employ a (1+1)-ES and are implemented in Pythonusing the machine learning library scikit-learn. The examples are conducted ontypical benchmark problems illustrating algorithmic concepts and theirexperimental behavior. The book closes with a discussion of related lines ofresearch.