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Towards a New Evolutionary Computation

Overview of attention for book
Cover of 'Towards a New Evolutionary Computation'

Table of Contents

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    Book Overview
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    Chapter 1 Linking Entropy to Estimation of Distribution Algorithms
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    Chapter 2 Entropy-based Convergence Measurement in Discrete Estimation of Distribution Algorithms
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    Chapter 3 Real-coded Bayesian Optimization Algorithm
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    Chapter 4 The CMA Evolution Strategy: A Comparing Review
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    Chapter 5 Estimation of Distribution Programming: EDA-based Approach to Program Generation
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    Chapter 6 Multi-objective Optimization with the Naive $$ \mathbb{M} $$ ID $$ \mathbb{E} $$ A
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    Chapter 7 A Parallel Island Model for Estimation of Distribution Algorithms
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    Chapter 8 GA-EDA: A New Hybrid Cooperative Search Evolutionary Algorithm
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    Chapter 9 Bayesian Classifiers in Optimization: An EDA-like Approach
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    Chapter 10 Feature Ranking Using an EDA-based Wrapper Approach
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    Chapter 11 Learning Linguistic Fuzzy Rules by Using Estimation of Distribution Algorithms as the Search Engine in the COR Methodology
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    Chapter 12 Estimation of Distribution Algorithm with 2-opt Local Search for the Quadratic Assignment Problem
Attention for Chapter 9: Bayesian Classifiers in Optimization: An EDA-like Approach
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Citations

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Chapter title
Bayesian Classifiers in Optimization: An EDA-like Approach
Chapter number 9
Book title
Towards a New Evolutionary Computation
Published by
Springer, Berlin, Heidelberg, January 2006
DOI 10.1007/3-540-32494-1_9
Book ISBNs
978-3-54-029006-3, 978-3-54-032494-2
Authors

Teresa Miquélez, Endika Bengoetxea, Pedro Larrañaga, Miquélez, Teresa, Bengoetxea, Endika, Larrañaga, Pedro

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 50%
Unknown 1 50%

Demographic breakdown

Readers by professional status Count As %
Professor 1 50%
Researcher 1 50%
Readers by discipline Count As %
Computer Science 2 100%

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