Simulated Evolution and Learning, Yuhui Shi; Kay Chen Tan; Mengjie Zhang; Ke Tang; X

Автор: Hime Aguiar e Oliveira Junior; Lester Ingber; Anto
Название: Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing
ISBN: 364243343X ISBN-13(EAN): 9783642433436
Издательство: Springer
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Цена: 121890.00 T
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Описание: With applications to many areas in science and technology, the technique examined in this volume is a highly effective algorithmic problem-solving tool. Contributions from leading experts cover the latest research and provide detailed examples of its use.

Автор: Robert M. French; Jacques P. Sougne
Название: Connectionist Models of Learning, Development and Evolution
ISBN: 1852333545 ISBN-13(EAN): 9781852333546
Издательство: Springer
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Цена: 102480.00 T
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Описание: Presents neural network modelling in the areas of evolution, learning, and development. This book, organized in six sections, covers the neural basis of cognition; development and category learning; implicit learning; social cognition; and, semantics. It also covers artificial intelligence, mathematics, psychology, neurobiology, and philosophy.

Автор: Kramer
Название: Machine Learning for Evolution Strategies
ISBN: 331933381X ISBN-13(EAN): 9783319333816
Издательство: Springer
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Цена: 113190.00 T
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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.

Автор: J.D. Becker; I. Eisele; F.W. M?ndemann
Название: Parallelism, Learning, Evolution
ISBN: 3540550275 ISBN-13(EAN): 9783540550273
Издательство: Springer
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Цена: 93160.00 T
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Описание: This volume presents the proceedings of two workshops: one on parallel processing, logic, organization and technology, and the other on evolutionary computer strategies. The papers explore a range of questions that are of interest to those involved in parallel processing research.